8 Commits

Author SHA1 Message Date
Andi Brae
b33496841b Move example skills into dedicated folder and create minimal top-level folder structure 2025-12-01 12:36:09 -05:00
Keith Lazuka
0f77e501e6 Update example skills and rename 'artifacts-builder' (#112)
* Export updated examples

* Rename 'artifacts-builder' to 'web-artifacts-builder'
2025-11-17 16:34:29 -05:00
Keith Lazuka
e5c60158df Add 'frontend-design' example skill (#98) 2025-11-12 12:58:13 -05:00
Mahesh Murag
c74d647e56 Clarify Claude Code installation in README.md (#20)
* Updates to README.md
2025-10-18 12:39:45 -04:00
Mahesh Murag
0877baec7e Updates to README.md (#9) 2025-10-16 15:15:19 -04:00
Keith Lazuka
b118d29ea4 Add Claude Claude instructions to the readme (#8) 2025-10-16 12:57:23 -04:00
Keith Lazuka
4d1e3f3f78 Add Claude Code Marketplace (#5) 2025-10-16 12:11:41 -04:00
Matt Piccolella
9b6100367b Small tweak to blog link (#7) 2025-10-16 12:08:28 -04:00
301 changed files with 1950 additions and 2890 deletions

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@@ -15,10 +15,10 @@
"source": "./",
"strict": false,
"skills": [
"./document-skills/xlsx",
"./document-skills/docx",
"./document-skills/pptx",
"./document-skills/pdf"
"./skills/xlsx",
"./skills/docx",
"./skills/pptx",
"./skills/pdf"
]
},
{
@@ -27,16 +27,17 @@
"source": "./",
"strict": false,
"skills": [
"./skill-creator",
"./mcp-builder",
"./canvas-design",
"./algorithmic-art",
"./internal-comms",
"./webapp-testing",
"./artifacts-builder",
"./slack-gif-creator",
"./theme-factory",
"./brand-guidelines"
"./skills/algorithmic-art",
"./skills/brand-guidelines",
"./skills/canvas-design",
"./skills/frontend-design",
"./skills/internal-comms",
"./skills/mcp-builder",
"./skills/skill-creator",
"./skills/slack-gif-creator",
"./skills/theme-factory",
"./skills/web-artifacts-builder",
"./skills/webapp-testing"
]
}
]

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@@ -5,53 +5,56 @@ For more information, check out:
- [What are skills?](https://support.claude.com/en/articles/12512176-what-are-skills)
- [Using skills in Claude](https://support.claude.com/en/articles/12512180-using-skills-in-claude)
- [How to create custom skills](https://support.claude.com/en/articles/12512198-creating-custom-skills)
- [Equipping agents for the real world with Skills](https://anthropic.com/engineering/equipping-agents-for-the-real-world-with-skills)
- [Equipping agents for the real world with Agent Skills](https://anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills)
# About This Repository
This repository contains example skills that demonstrate what's possible with Claude's skills system. These examples range from creative applications (art, music, design) to technical tasks (testing web apps, MCP server generation) to enterprise workflows (communications, branding, etc.).
This repository contains skills that demonstrate what's possible with Claude's skills system. These skills range from creative applications (art, music, design) to technical tasks (testing web apps, MCP server generation) to enterprise workflows (communications, branding, etc.).
Each skill is self-contained in its own directory with a `SKILL.md` file containing the instructions and metadata that Claude uses. Browse through these examples to get inspiration for your own skills or to understand different patterns and approaches.
Each skill is self-contained in its own folder with a `SKILL.md` file containing the instructions and metadata that Claude uses. Browse through these skills to get inspiration for your own skills or to understand different patterns and approaches.
**Note:** These are reference examples for inspiration and learning. They showcase general-purpose capabilities rather than organization-specific workflows or sensitive content.
Many skills in this repo are open source (Apache 2.0). We've also included the document creation & editing skills that power [Claude's document capabilities](https://www.anthropic.com/news/create-files) under the hood in the [`skills/docx`](./skills/docx), [`skills/pdf`](./skills/pdf), [`skills/pptx`](./skills/pptx), and [`skills/xlsx`](./skills/xlsx) subfolders. These are source-available, not open source, but we wanted to share these with developers as a reference for more complex skills that are actively used in a production AI application.
## Disclaimer
**These skills are provided for demonstration and educational purposes only.** While some of these capabilities may be available in Claude, the implementations and behaviors you receive from Claude may differ from what is shown in these examples. These examples are meant to illustrate patterns and possibilities. Always test skills thoroughly in your own environment before relying on them for critical tasks.
**These skills are provided for demonstration and educational purposes only.** While some of these capabilities may be available in Claude, the implementations and behaviors you receive from Claude may differ from what is shown in these skills. These skills are meant to illustrate patterns and possibilities. Always test skills thoroughly in your own environment before relying on them for critical tasks.
# Example Skills
# Skill Sets
- [./skills](./skills): Skill examples for Creative & Design, Development & Technical, Enterprise & Communication, and Document Skills
- [./spec](./spec): The Agent Skills specification
- [./template](./template): Skill template
This repository includes a diverse collection of example skills demonstrating different capabilities:
# Try in Claude Code, Claude.ai, and the API
## Creative & Design
- **algorithmic-art** - Create generative art using p5.js with seeded randomness, flow fields, and particle systems
- **canvas-design** - Design beautiful visual art in .png and .pdf formats using design philosophies
- **slack-gif-creator** - Create animated GIFs optimized for Slack's size constraints
## Claude Code
You can register this repository as a Claude Code Plugin marketplace by running the following command in Claude Code:
```
/plugin marketplace add anthropics/skills
```
## Development & Technical
- **artifacts-builder** - Build complex claude.ai HTML artifacts using React, Tailwind CSS, and shadcn/ui components
- **mcp-server** - Guide for creating high-quality MCP servers to integrate external APIs and services
- **webapp-testing** - Test local web applications using Playwright for UI verification and debugging
Then, to install a specific set of skills:
1. Select `Browse and install plugins`
2. Select `anthropic-agent-skills`
3. Select `document-skills` or `example-skills`
4. Select `Install now`
## Enterprise & Communication
- **brand-guidelines** - Apply Anthropic's official brand colors and typography to artifacts
- **internal-comms** - Write internal communications like status reports, newsletters, and FAQs
- **theme-factory** - Style artifacts with 10 pre-set professional themes or generate custom themes on-the-fly
Alternatively, directly install either Plugin via:
```
/plugin install document-skills@anthropic-agent-skills
/plugin install example-skills@anthropic-agent-skills
```
## Meta Skills
- **skill-creator** - Guide for creating effective skills that extend Claude's capabilities
- **template-skill** - A basic template to use as a starting point for new skills
After installing the plugin, you can use the skill by just mentioning it. For instance, if you install the `document-skills` plugin from the marketplace, you can ask Claude Code to do something like: "Use the PDF skill to extract the form fields from `path/to/some-file.pdf`"
# Document Skills
## Claude.ai
The `document-skills/` subdirectory contains skills that Anthropic developed to help Claude create various document file formats. These skills demonstrate advanced patterns for working with complex file formats and binary data:
These example skills are all already available to paid plans in Claude.ai.
- **docx** - Create, edit, and analyze Word documents with support for tracked changes, comments, formatting preservation, and text extraction
- **pdf** - Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms
- **pptx** - Create, edit, and analyze PowerPoint presentations with support for layouts, templates, charts, and automated slide generation
- **xlsx** - Create, edit, and analyze Excel spreadsheets with support for formulas, formatting, data analysis, and visualization
To use any skill from this repository or upload custom skills, follow the instructions in [Using skills in Claude](https://support.claude.com/en/articles/12512180-using-skills-in-claude#h_a4222fa77b).
**Important Disclaimer:** These document skills are point-in-time snapshots and are not actively maintained or updated. Versions of these skills ship pre-included with Claude. They are primarily intended as reference examples to illustrate how Anthropic approaches developing more complex skills that work with binary file formats and document structures.
## Claude API
You can use Anthropic's pre-built skills, and upload custom skills, via the Claude API. See the [Skills API Quickstart](https://docs.claude.com/en/api/skills-guide#creating-a-skill) for more.
# Creating a Basic Skill
@@ -86,4 +89,4 @@ The markdown content below contains the instructions, examples, and guidelines t
Skills are a great way to teach Claude how to get better at using specific pieces of software. As we see awesome example skills from partners, we may highlight some of them here:
- **Notion** - [Notion Skills for Claude](https://www.notion.so/notiondevs/Notion-Skills-for-Claude-28da4445d27180c7af1df7d8615723d0)
- **Notion** - [Notion Skills for Claude](https://www.notion.so/notiondevs/Notion-Skills-for-Claude-28da4445d27180c7af1df7d8615723d0)

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@@ -1,328 +0,0 @@
---
name: mcp-builder
description: Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
license: Complete terms in LICENSE.txt
---
# MCP Server Development Guide
## Overview
To create high-quality MCP (Model Context Protocol) servers that enable LLMs to effectively interact with external services, use this skill. An MCP server provides tools that allow LLMs to access external services and APIs. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks using the tools provided.
---
# Process
## 🚀 High-Level Workflow
Creating a high-quality MCP server involves four main phases:
### Phase 1: Deep Research and Planning
#### 1.1 Understand Agent-Centric Design Principles
Before diving into implementation, understand how to design tools for AI agents by reviewing these principles:
**Build for Workflows, Not Just API Endpoints:**
- Don't simply wrap existing API endpoints - build thoughtful, high-impact workflow tools
- Consolidate related operations (e.g., `schedule_event` that both checks availability and creates event)
- Focus on tools that enable complete tasks, not just individual API calls
- Consider what workflows agents actually need to accomplish
**Optimize for Limited Context:**
- Agents have constrained context windows - make every token count
- Return high-signal information, not exhaustive data dumps
- Provide "concise" vs "detailed" response format options
- Default to human-readable identifiers over technical codes (names over IDs)
- Consider the agent's context budget as a scarce resource
**Design Actionable Error Messages:**
- Error messages should guide agents toward correct usage patterns
- Suggest specific next steps: "Try using filter='active_only' to reduce results"
- Make errors educational, not just diagnostic
- Help agents learn proper tool usage through clear feedback
**Follow Natural Task Subdivisions:**
- Tool names should reflect how humans think about tasks
- Group related tools with consistent prefixes for discoverability
- Design tools around natural workflows, not just API structure
**Use Evaluation-Driven Development:**
- Create realistic evaluation scenarios early
- Let agent feedback drive tool improvements
- Prototype quickly and iterate based on actual agent performance
#### 1.3 Study MCP Protocol Documentation
**Fetch the latest MCP protocol documentation:**
Use WebFetch to load: `https://modelcontextprotocol.io/llms-full.txt`
This comprehensive document contains the complete MCP specification and guidelines.
#### 1.4 Study Framework Documentation
**Load and read the following reference files:**
- **MCP Best Practices**: [📋 View Best Practices](./reference/mcp_best_practices.md) - Core guidelines for all MCP servers
**For Python implementations, also load:**
- **Python SDK Documentation**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md`
- [🐍 Python Implementation Guide](./reference/python_mcp_server.md) - Python-specific best practices and examples
**For Node/TypeScript implementations, also load:**
- **TypeScript SDK Documentation**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md`
- [⚡ TypeScript Implementation Guide](./reference/node_mcp_server.md) - Node/TypeScript-specific best practices and examples
#### 1.5 Exhaustively Study API Documentation
To integrate a service, read through **ALL** available API documentation:
- Official API reference documentation
- Authentication and authorization requirements
- Rate limiting and pagination patterns
- Error responses and status codes
- Available endpoints and their parameters
- Data models and schemas
**To gather comprehensive information, use web search and the WebFetch tool as needed.**
#### 1.6 Create a Comprehensive Implementation Plan
Based on your research, create a detailed plan that includes:
**Tool Selection:**
- List the most valuable endpoints/operations to implement
- Prioritize tools that enable the most common and important use cases
- Consider which tools work together to enable complex workflows
**Shared Utilities and Helpers:**
- Identify common API request patterns
- Plan pagination helpers
- Design filtering and formatting utilities
- Plan error handling strategies
**Input/Output Design:**
- Define input validation models (Pydantic for Python, Zod for TypeScript)
- Design consistent response formats (e.g., JSON or Markdown), and configurable levels of detail (e.g., Detailed or Concise)
- Plan for large-scale usage (thousands of users/resources)
- Implement character limits and truncation strategies (e.g., 25,000 tokens)
**Error Handling Strategy:**
- Plan graceful failure modes
- Design clear, actionable, LLM-friendly, natural language error messages which prompt further action
- Consider rate limiting and timeout scenarios
- Handle authentication and authorization errors
---
### Phase 2: Implementation
Now that you have a comprehensive plan, begin implementation following language-specific best practices.
#### 2.1 Set Up Project Structure
**For Python:**
- Create a single `.py` file or organize into modules if complex (see [🐍 Python Guide](./reference/python_mcp_server.md))
- Use the MCP Python SDK for tool registration
- Define Pydantic models for input validation
**For Node/TypeScript:**
- Create proper project structure (see [⚡ TypeScript Guide](./reference/node_mcp_server.md))
- Set up `package.json` and `tsconfig.json`
- Use MCP TypeScript SDK
- Define Zod schemas for input validation
#### 2.2 Implement Core Infrastructure First
**To begin implementation, create shared utilities before implementing tools:**
- API request helper functions
- Error handling utilities
- Response formatting functions (JSON and Markdown)
- Pagination helpers
- Authentication/token management
#### 2.3 Implement Tools Systematically
For each tool in the plan:
**Define Input Schema:**
- Use Pydantic (Python) or Zod (TypeScript) for validation
- Include proper constraints (min/max length, regex patterns, min/max values, ranges)
- Provide clear, descriptive field descriptions
- Include diverse examples in field descriptions
**Write Comprehensive Docstrings/Descriptions:**
- One-line summary of what the tool does
- Detailed explanation of purpose and functionality
- Explicit parameter types with examples
- Complete return type schema
- Usage examples (when to use, when not to use)
- Error handling documentation, which outlines how to proceed given specific errors
**Implement Tool Logic:**
- Use shared utilities to avoid code duplication
- Follow async/await patterns for all I/O
- Implement proper error handling
- Support multiple response formats (JSON and Markdown)
- Respect pagination parameters
- Check character limits and truncate appropriately
**Add Tool Annotations:**
- `readOnlyHint`: true (for read-only operations)
- `destructiveHint`: false (for non-destructive operations)
- `idempotentHint`: true (if repeated calls have same effect)
- `openWorldHint`: true (if interacting with external systems)
#### 2.4 Follow Language-Specific Best Practices
**At this point, load the appropriate language guide:**
**For Python: Load [🐍 Python Implementation Guide](./reference/python_mcp_server.md) and ensure the following:**
- Using MCP Python SDK with proper tool registration
- Pydantic v2 models with `model_config`
- Type hints throughout
- Async/await for all I/O operations
- Proper imports organization
- Module-level constants (CHARACTER_LIMIT, API_BASE_URL)
**For Node/TypeScript: Load [⚡ TypeScript Implementation Guide](./reference/node_mcp_server.md) and ensure the following:**
- Using `server.registerTool` properly
- Zod schemas with `.strict()`
- TypeScript strict mode enabled
- No `any` types - use proper types
- Explicit Promise<T> return types
- Build process configured (`npm run build`)
---
### Phase 3: Review and Refine
After initial implementation:
#### 3.1 Code Quality Review
To ensure quality, review the code for:
- **DRY Principle**: No duplicated code between tools
- **Composability**: Shared logic extracted into functions
- **Consistency**: Similar operations return similar formats
- **Error Handling**: All external calls have error handling
- **Type Safety**: Full type coverage (Python type hints, TypeScript types)
- **Documentation**: Every tool has comprehensive docstrings/descriptions
#### 3.2 Test and Build
**Important:** MCP servers are long-running processes that wait for requests over stdio/stdin or sse/http. Running them directly in your main process (e.g., `python server.py` or `node dist/index.js`) will cause your process to hang indefinitely.
**Safe ways to test the server:**
- Use the evaluation harness (see Phase 4) - recommended approach
- Run the server in tmux to keep it outside your main process
- Use a timeout when testing: `timeout 5s python server.py`
**For Python:**
- Verify Python syntax: `python -m py_compile your_server.py`
- Check imports work correctly by reviewing the file
- To manually test: Run server in tmux, then test with evaluation harness in main process
- Or use the evaluation harness directly (it manages the server for stdio transport)
**For Node/TypeScript:**
- Run `npm run build` and ensure it completes without errors
- Verify dist/index.js is created
- To manually test: Run server in tmux, then test with evaluation harness in main process
- Or use the evaluation harness directly (it manages the server for stdio transport)
#### 3.3 Use Quality Checklist
To verify implementation quality, load the appropriate checklist from the language-specific guide:
- Python: see "Quality Checklist" in [🐍 Python Guide](./reference/python_mcp_server.md)
- Node/TypeScript: see "Quality Checklist" in [⚡ TypeScript Guide](./reference/node_mcp_server.md)
---
### Phase 4: Create Evaluations
After implementing your MCP server, create comprehensive evaluations to test its effectiveness.
**Load [✅ Evaluation Guide](./reference/evaluation.md) for complete evaluation guidelines.**
#### 4.1 Understand Evaluation Purpose
Evaluations test whether LLMs can effectively use your MCP server to answer realistic, complex questions.
#### 4.2 Create 10 Evaluation Questions
To create effective evaluations, follow the process outlined in the evaluation guide:
1. **Tool Inspection**: List available tools and understand their capabilities
2. **Content Exploration**: Use READ-ONLY operations to explore available data
3. **Question Generation**: Create 10 complex, realistic questions
4. **Answer Verification**: Solve each question yourself to verify answers
#### 4.3 Evaluation Requirements
Each question must be:
- **Independent**: Not dependent on other questions
- **Read-only**: Only non-destructive operations required
- **Complex**: Requiring multiple tool calls and deep exploration
- **Realistic**: Based on real use cases humans would care about
- **Verifiable**: Single, clear answer that can be verified by string comparison
- **Stable**: Answer won't change over time
#### 4.4 Output Format
Create an XML file with this structure:
```xml
<evaluation>
<qa_pair>
<question>Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat?</question>
<answer>3</answer>
</qa_pair>
<!-- More qa_pairs... -->
</evaluation>
```
---
# Reference Files
## 📚 Documentation Library
Load these resources as needed during development:
### Core MCP Documentation (Load First)
- **MCP Protocol**: Fetch from `https://modelcontextprotocol.io/llms-full.txt` - Complete MCP specification
- [📋 MCP Best Practices](./reference/mcp_best_practices.md) - Universal MCP guidelines including:
- Server and tool naming conventions
- Response format guidelines (JSON vs Markdown)
- Pagination best practices
- Character limits and truncation strategies
- Tool development guidelines
- Security and error handling standards
### SDK Documentation (Load During Phase 1/2)
- **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md`
- **TypeScript SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md`
### Language-Specific Implementation Guides (Load During Phase 2)
- [🐍 Python Implementation Guide](./reference/python_mcp_server.md) - Complete Python/FastMCP guide with:
- Server initialization patterns
- Pydantic model examples
- Tool registration with `@mcp.tool`
- Complete working examples
- Quality checklist
- [⚡ TypeScript Implementation Guide](./reference/node_mcp_server.md) - Complete TypeScript guide with:
- Project structure
- Zod schema patterns
- Tool registration with `server.registerTool`
- Complete working examples
- Quality checklist
### Evaluation Guide (Load During Phase 4)
- [✅ Evaluation Guide](./reference/evaluation.md) - Complete evaluation creation guide with:
- Question creation guidelines
- Answer verification strategies
- XML format specifications
- Example questions and answers
- Running an evaluation with the provided scripts

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@@ -1,915 +0,0 @@
# MCP Server Development Best Practices and Guidelines
## Overview
This document compiles essential best practices and guidelines for building Model Context Protocol (MCP) servers. It covers naming conventions, tool design, response formats, pagination, error handling, security, and compliance requirements.
---
## Quick Reference
### Server Naming
- **Python**: `{service}_mcp` (e.g., `slack_mcp`)
- **Node/TypeScript**: `{service}-mcp-server` (e.g., `slack-mcp-server`)
### Tool Naming
- Use snake_case with service prefix
- Format: `{service}_{action}_{resource}`
- Example: `slack_send_message`, `github_create_issue`
### Response Formats
- Support both JSON and Markdown formats
- JSON for programmatic processing
- Markdown for human readability
### Pagination
- Always respect `limit` parameter
- Return `has_more`, `next_offset`, `total_count`
- Default to 20-50 items
### Character Limits
- Set CHARACTER_LIMIT constant (typically 25,000)
- Truncate gracefully with clear messages
- Provide guidance on filtering
---
## Table of Contents
1. Server Naming Conventions
2. Tool Naming and Design
3. Response Format Guidelines
4. Pagination Best Practices
5. Character Limits and Truncation
6. Tool Development Best Practices
7. Transport Best Practices
8. Testing Requirements
9. OAuth and Security Best Practices
10. Resource Management Best Practices
11. Prompt Management Best Practices
12. Error Handling Standards
13. Documentation Requirements
14. Compliance and Monitoring
---
## 1. Server Naming Conventions
Follow these standardized naming patterns for MCP servers:
**Python**: Use format `{service}_mcp` (lowercase with underscores)
- Examples: `slack_mcp`, `github_mcp`, `jira_mcp`, `stripe_mcp`
**Node/TypeScript**: Use format `{service}-mcp-server` (lowercase with hyphens)
- Examples: `slack-mcp-server`, `github-mcp-server`, `jira-mcp-server`
The name should be:
- General (not tied to specific features)
- Descriptive of the service/API being integrated
- Easy to infer from the task description
- Without version numbers or dates
---
## 2. Tool Naming and Design
### Tool Naming Best Practices
1. **Use snake_case**: `search_users`, `create_project`, `get_channel_info`
2. **Include service prefix**: Anticipate that your MCP server may be used alongside other MCP servers
- Use `slack_send_message` instead of just `send_message`
- Use `github_create_issue` instead of just `create_issue`
- Use `asana_list_tasks` instead of just `list_tasks`
3. **Be action-oriented**: Start with verbs (get, list, search, create, etc.)
4. **Be specific**: Avoid generic names that could conflict with other servers
5. **Maintain consistency**: Use consistent naming patterns within your server
### Tool Design Guidelines
- Tool descriptions must narrowly and unambiguously describe functionality
- Descriptions must precisely match actual functionality
- Should not create confusion with other MCP servers
- Should provide tool annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint)
- Keep tool operations focused and atomic
---
## 3. Response Format Guidelines
All tools that return data should support multiple formats for flexibility:
### JSON Format (`response_format="json"`)
- Machine-readable structured data
- Include all available fields and metadata
- Consistent field names and types
- Suitable for programmatic processing
- Use for when LLMs need to process data further
### Markdown Format (`response_format="markdown"`, typically default)
- Human-readable formatted text
- Use headers, lists, and formatting for clarity
- Convert timestamps to human-readable format (e.g., "2024-01-15 10:30:00 UTC" instead of epoch)
- Show display names with IDs in parentheses (e.g., "@john.doe (U123456)")
- Omit verbose metadata (e.g., show only one profile image URL, not all sizes)
- Group related information logically
- Use for when presenting information to users
---
## 4. Pagination Best Practices
For tools that list resources:
- **Always respect the `limit` parameter**: Never load all results when a limit is specified
- **Implement pagination**: Use `offset` or cursor-based pagination
- **Return pagination metadata**: Include `has_more`, `next_offset`/`next_cursor`, `total_count`
- **Never load all results into memory**: Especially important for large datasets
- **Default to reasonable limits**: 20-50 items is typical
- **Include clear pagination info in responses**: Make it easy for LLMs to request more data
Example pagination response structure:
```json
{
"total": 150,
"count": 20,
"offset": 0,
"items": [...],
"has_more": true,
"next_offset": 20
}
```
---
## 5. Character Limits and Truncation
To prevent overwhelming responses with too much data:
- **Define CHARACTER_LIMIT constant**: Typically 25,000 characters at module level
- **Check response size before returning**: Measure the final response length
- **Truncate gracefully with clear indicators**: Let the LLM know data was truncated
- **Provide guidance on filtering**: Suggest how to use parameters to reduce results
- **Include truncation metadata**: Show what was truncated and how to get more
Example truncation handling:
```python
CHARACTER_LIMIT = 25000
if len(result) > CHARACTER_LIMIT:
truncated_data = data[:max(1, len(data) // 2)]
response["truncated"] = True
response["truncation_message"] = (
f"Response truncated from {len(data)} to {len(truncated_data)} items. "
f"Use 'offset' parameter or add filters to see more results."
)
```
---
## 6. Transport Options
MCP servers support multiple transport mechanisms for different deployment scenarios:
### Stdio Transport
**Best for**: Command-line tools, local integrations, subprocess execution
**Characteristics**:
- Standard input/output stream communication
- Simple setup, no network configuration needed
- Runs as a subprocess of the client
- Ideal for desktop applications and CLI tools
**Use when**:
- Building tools for local development environments
- Integrating with desktop applications (e.g., Claude Desktop)
- Creating command-line utilities
- Single-user, single-session scenarios
### HTTP Transport
**Best for**: Web services, remote access, multi-client scenarios
**Characteristics**:
- Request-response pattern over HTTP
- Supports multiple simultaneous clients
- Can be deployed as a web service
- Requires network configuration and security considerations
**Use when**:
- Serving multiple clients simultaneously
- Deploying as a cloud service
- Integration with web applications
- Need for load balancing or scaling
### Server-Sent Events (SSE) Transport
**Best for**: Real-time updates, push notifications, streaming data
**Characteristics**:
- One-way server-to-client streaming over HTTP
- Enables real-time updates without polling
- Long-lived connections for continuous data flow
- Built on standard HTTP infrastructure
**Use when**:
- Clients need real-time data updates
- Implementing push notifications
- Streaming logs or monitoring data
- Progressive result delivery for long operations
### Transport Selection Criteria
| Criterion | Stdio | HTTP | SSE |
|-----------|-------|------|-----|
| **Deployment** | Local | Remote | Remote |
| **Clients** | Single | Multiple | Multiple |
| **Communication** | Bidirectional | Request-Response | Server-Push |
| **Complexity** | Low | Medium | Medium-High |
| **Real-time** | No | No | Yes |
---
## 7. Tool Development Best Practices
### General Guidelines
1. Tool names should be descriptive and action-oriented
2. Use parameter validation with detailed JSON schemas
3. Include examples in tool descriptions
4. Implement proper error handling and validation
5. Use progress reporting for long operations
6. Keep tool operations focused and atomic
7. Document expected return value structures
8. Implement proper timeouts
9. Consider rate limiting for resource-intensive operations
10. Log tool usage for debugging and monitoring
### Security Considerations for Tools
#### Input Validation
- Validate all parameters against schema
- Sanitize file paths and system commands
- Validate URLs and external identifiers
- Check parameter sizes and ranges
- Prevent command injection
#### Access Control
- Implement authentication where needed
- Use appropriate authorization checks
- Audit tool usage
- Rate limit requests
- Monitor for abuse
#### Error Handling
- Don't expose internal errors to clients
- Log security-relevant errors
- Handle timeouts appropriately
- Clean up resources after errors
- Validate return values
### Tool Annotations
- Provide readOnlyHint and destructiveHint annotations
- Remember annotations are hints, not security guarantees
- Clients should not make security-critical decisions based solely on annotations
---
## 8. Transport Best Practices
### General Transport Guidelines
1. Handle connection lifecycle properly
2. Implement proper error handling
3. Use appropriate timeout values
4. Implement connection state management
5. Clean up resources on disconnection
### Security Best Practices for Transport
- Follow security considerations for DNS rebinding attacks
- Implement proper authentication mechanisms
- Validate message formats
- Handle malformed messages gracefully
### Stdio Transport Specific
- Local MCP servers should NOT log to stdout (interferes with protocol)
- Use stderr for logging messages
- Handle standard I/O streams properly
---
## 9. Testing Requirements
A comprehensive testing strategy should cover:
### Functional Testing
- Verify correct execution with valid/invalid inputs
### Integration Testing
- Test interaction with external systems
### Security Testing
- Validate auth, input sanitization, rate limiting
### Performance Testing
- Check behavior under load, timeouts
### Error Handling
- Ensure proper error reporting and cleanup
---
## 10. OAuth and Security Best Practices
### Authentication and Authorization
MCP servers that connect to external services should implement proper authentication:
**OAuth 2.1 Implementation:**
- Use secure OAuth 2.1 with certificates from recognized authorities
- Validate access tokens before processing requests
- Only accept tokens specifically intended for your server
- Reject tokens without proper audience claims
- Never pass through tokens received from MCP clients
**API Key Management:**
- Store API keys in environment variables, never in code
- Validate keys on server startup
- Provide clear error messages when authentication fails
- Use secure transmission for sensitive credentials
### Input Validation and Security
**Always validate inputs:**
- Sanitize file paths to prevent directory traversal
- Validate URLs and external identifiers
- Check parameter sizes and ranges
- Prevent command injection in system calls
- Use schema validation (Pydantic/Zod) for all inputs
**Error handling security:**
- Don't expose internal errors to clients
- Log security-relevant errors server-side
- Provide helpful but not revealing error messages
- Clean up resources after errors
### Privacy and Data Protection
**Data collection principles:**
- Only collect data strictly necessary for functionality
- Don't collect extraneous conversation data
- Don't collect PII unless explicitly required for the tool's purpose
- Provide clear information about what data is accessed
**Data transmission:**
- Don't send data to servers outside your organization without disclosure
- Use secure transmission (HTTPS) for all network communication
- Validate certificates for external services
---
## 11. Resource Management Best Practices
1. Only suggest necessary resources
2. Use clear, descriptive names for roots
3. Handle resource boundaries properly
4. Respect client control over resources
5. Use model-controlled primitives (tools) for automatic data exposure
---
## 12. Prompt Management Best Practices
- Clients should show users proposed prompts
- Users should be able to modify or reject prompts
- Clients should show users completions
- Users should be able to modify or reject completions
- Consider costs when using sampling
---
## 13. Error Handling Standards
- Use standard JSON-RPC error codes
- Report tool errors within result objects (not protocol-level)
- Provide helpful, specific error messages
- Don't expose internal implementation details
- Clean up resources properly on errors
---
## 14. Documentation Requirements
- Provide clear documentation of all tools and capabilities
- Include working examples (at least 3 per major feature)
- Document security considerations
- Specify required permissions and access levels
- Document rate limits and performance characteristics
---
## 15. Compliance and Monitoring
- Implement logging for debugging and monitoring
- Track tool usage patterns
- Monitor for potential abuse
- Maintain audit trails for security-relevant operations
- Be prepared for ongoing compliance reviews
---
## Summary
These best practices represent the comprehensive guidelines for building secure, efficient, and compliant MCP servers that work well within the ecosystem. Developers should follow these guidelines to ensure their MCP servers meet the standards for inclusion in the MCP directory and provide a safe, reliable experience for users.
----------
# Tools
> Enable LLMs to perform actions through your server
Tools are a powerful primitive in the Model Context Protocol (MCP) that enable servers to expose executable functionality to clients. Through tools, LLMs can interact with external systems, perform computations, and take actions in the real world.
<Note>
Tools are designed to be **model-controlled**, meaning that tools are exposed from servers to clients with the intention of the AI model being able to automatically invoke them (with a human in the loop to grant approval).
</Note>
## Overview
Tools in MCP allow servers to expose executable functions that can be invoked by clients and used by LLMs to perform actions. Key aspects of tools include:
* **Discovery**: Clients can obtain a list of available tools by sending a `tools/list` request
* **Invocation**: Tools are called using the `tools/call` request, where servers perform the requested operation and return results
* **Flexibility**: Tools can range from simple calculations to complex API interactions
Like [resources](/docs/concepts/resources), tools are identified by unique names and can include descriptions to guide their usage. However, unlike resources, tools represent dynamic operations that can modify state or interact with external systems.
## Tool definition structure
Each tool is defined with the following structure:
```typescript
{
name: string; // Unique identifier for the tool
description?: string; // Human-readable description
inputSchema: { // JSON Schema for the tool's parameters
type: "object",
properties: { ... } // Tool-specific parameters
},
annotations?: { // Optional hints about tool behavior
title?: string; // Human-readable title for the tool
readOnlyHint?: boolean; // If true, the tool does not modify its environment
destructiveHint?: boolean; // If true, the tool may perform destructive updates
idempotentHint?: boolean; // If true, repeated calls with same args have no additional effect
openWorldHint?: boolean; // If true, tool interacts with external entities
}
}
```
## Implementing tools
Here's an example of implementing a basic tool in an MCP server:
<Tabs>
<Tab title="TypeScript">
```typescript
const server = new Server({
name: "example-server",
version: "1.0.0"
}, {
capabilities: {
tools: {}
}
});
// Define available tools
server.setRequestHandler(ListToolsRequestSchema, async () => {
return {
tools: [{
name: "calculate_sum",
description: "Add two numbers together",
inputSchema: {
type: "object",
properties: {
a: { type: "number" },
b: { type: "number" }
},
required: ["a", "b"]
}
}]
};
});
// Handle tool execution
server.setRequestHandler(CallToolRequestSchema, async (request) => {
if (request.params.name === "calculate_sum") {
const { a, b } = request.params.arguments;
return {
content: [
{
type: "text",
text: String(a + b)
}
]
};
}
throw new Error("Tool not found");
});
```
</Tab>
<Tab title="Python">
```python
app = Server("example-server")
@app.list_tools()
async def list_tools() -> list[types.Tool]:
return [
types.Tool(
name="calculate_sum",
description="Add two numbers together",
inputSchema={
"type": "object",
"properties": {
"a": {"type": "number"},
"b": {"type": "number"}
},
"required": ["a", "b"]
}
)
]
@app.call_tool()
async def call_tool(
name: str,
arguments: dict
) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
if name == "calculate_sum":
a = arguments["a"]
b = arguments["b"]
result = a + b
return [types.TextContent(type="text", text=str(result))]
raise ValueError(f"Tool not found: {name}")
```
</Tab>
</Tabs>
## Example tool patterns
Here are some examples of types of tools that a server could provide:
### System operations
Tools that interact with the local system:
```typescript
{
name: "execute_command",
description: "Run a shell command",
inputSchema: {
type: "object",
properties: {
command: { type: "string" },
args: { type: "array", items: { type: "string" } }
}
}
}
```
### API integrations
Tools that wrap external APIs:
```typescript
{
name: "github_create_issue",
description: "Create a GitHub issue",
inputSchema: {
type: "object",
properties: {
title: { type: "string" },
body: { type: "string" },
labels: { type: "array", items: { type: "string" } }
}
}
}
```
### Data processing
Tools that transform or analyze data:
```typescript
{
name: "analyze_csv",
description: "Analyze a CSV file",
inputSchema: {
type: "object",
properties: {
filepath: { type: "string" },
operations: {
type: "array",
items: {
enum: ["sum", "average", "count"]
}
}
}
}
}
```
## Best practices
When implementing tools:
1. Provide clear, descriptive names and descriptions
2. Use detailed JSON Schema definitions for parameters
3. Include examples in tool descriptions to demonstrate how the model should use them
4. Implement proper error handling and validation
5. Use progress reporting for long operations
6. Keep tool operations focused and atomic
7. Document expected return value structures
8. Implement proper timeouts
9. Consider rate limiting for resource-intensive operations
10. Log tool usage for debugging and monitoring
### Tool name conflicts
MCP client applications and MCP server proxies may encounter tool name conflicts when building their own tool lists. For example, two connected MCP servers `web1` and `web2` may both expose a tool named `search_web`.
Applications may disambiguiate tools with one of the following strategies (among others; not an exhaustive list):
* Concatenating a unique, user-defined server name with the tool name, e.g. `web1___search_web` and `web2___search_web`. This strategy may be preferable when unique server names are already provided by the user in a configuration file.
* Generating a random prefix for the tool name, e.g. `jrwxs___search_web` and `6cq52___search_web`. This strategy may be preferable in server proxies where user-defined unique names are not available.
* Using the server URI as a prefix for the tool name, e.g. `web1.example.com:search_web` and `web2.example.com:search_web`. This strategy may be suitable when working with remote MCP servers.
Note that the server-provided name from the initialization flow is not guaranteed to be unique and is not generally suitable for disambiguation purposes.
## Security considerations
When exposing tools:
### Input validation
* Validate all parameters against the schema
* Sanitize file paths and system commands
* Validate URLs and external identifiers
* Check parameter sizes and ranges
* Prevent command injection
### Access control
* Implement authentication where needed
* Use appropriate authorization checks
* Audit tool usage
* Rate limit requests
* Monitor for abuse
### Error handling
* Don't expose internal errors to clients
* Log security-relevant errors
* Handle timeouts appropriately
* Clean up resources after errors
* Validate return values
## Tool discovery and updates
MCP supports dynamic tool discovery:
1. Clients can list available tools at any time
2. Servers can notify clients when tools change using `notifications/tools/list_changed`
3. Tools can be added or removed during runtime
4. Tool definitions can be updated (though this should be done carefully)
## Error handling
Tool errors should be reported within the result object, not as MCP protocol-level errors. This allows the LLM to see and potentially handle the error. When a tool encounters an error:
1. Set `isError` to `true` in the result
2. Include error details in the `content` array
Here's an example of proper error handling for tools:
<Tabs>
<Tab title="TypeScript">
```typescript
try {
// Tool operation
const result = performOperation();
return {
content: [
{
type: "text",
text: `Operation successful: ${result}`
}
]
};
} catch (error) {
return {
isError: true,
content: [
{
type: "text",
text: `Error: ${error.message}`
}
]
};
}
```
</Tab>
<Tab title="Python">
```python
try:
# Tool operation
result = perform_operation()
return types.CallToolResult(
content=[
types.TextContent(
type="text",
text=f"Operation successful: {result}"
)
]
)
except Exception as error:
return types.CallToolResult(
isError=True,
content=[
types.TextContent(
type="text",
text=f"Error: {str(error)}"
)
]
)
```
</Tab>
</Tabs>
This approach allows the LLM to see that an error occurred and potentially take corrective action or request human intervention.
## Tool annotations
Tool annotations provide additional metadata about a tool's behavior, helping clients understand how to present and manage tools. These annotations are hints that describe the nature and impact of a tool, but should not be relied upon for security decisions.
### Purpose of tool annotations
Tool annotations serve several key purposes:
1. Provide UX-specific information without affecting model context
2. Help clients categorize and present tools appropriately
3. Convey information about a tool's potential side effects
4. Assist in developing intuitive interfaces for tool approval
### Available tool annotations
The MCP specification defines the following annotations for tools:
| Annotation | Type | Default | Description |
| ----------------- | ------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------ |
| `title` | string | - | A human-readable title for the tool, useful for UI display |
| `readOnlyHint` | boolean | false | If true, indicates the tool does not modify its environment |
| `destructiveHint` | boolean | true | If true, the tool may perform destructive updates (only meaningful when `readOnlyHint` is false) |
| `idempotentHint` | boolean | false | If true, calling the tool repeatedly with the same arguments has no additional effect (only meaningful when `readOnlyHint` is false) |
| `openWorldHint` | boolean | true | If true, the tool may interact with an "open world" of external entities |
### Example usage
Here's how to define tools with annotations for different scenarios:
```typescript
// A read-only search tool
{
name: "web_search",
description: "Search the web for information",
inputSchema: {
type: "object",
properties: {
query: { type: "string" }
},
required: ["query"]
},
annotations: {
title: "Web Search",
readOnlyHint: true,
openWorldHint: true
}
}
// A destructive file deletion tool
{
name: "delete_file",
description: "Delete a file from the filesystem",
inputSchema: {
type: "object",
properties: {
path: { type: "string" }
},
required: ["path"]
},
annotations: {
title: "Delete File",
readOnlyHint: false,
destructiveHint: true,
idempotentHint: true,
openWorldHint: false
}
}
// A non-destructive database record creation tool
{
name: "create_record",
description: "Create a new record in the database",
inputSchema: {
type: "object",
properties: {
table: { type: "string" },
data: { type: "object" }
},
required: ["table", "data"]
},
annotations: {
title: "Create Database Record",
readOnlyHint: false,
destructiveHint: false,
idempotentHint: false,
openWorldHint: false
}
}
```
### Integrating annotations in server implementation
<Tabs>
<Tab title="TypeScript">
```typescript
server.setRequestHandler(ListToolsRequestSchema, async () => {
return {
tools: [{
name: "calculate_sum",
description: "Add two numbers together",
inputSchema: {
type: "object",
properties: {
a: { type: "number" },
b: { type: "number" }
},
required: ["a", "b"]
},
annotations: {
title: "Calculate Sum",
readOnlyHint: true,
openWorldHint: false
}
}]
};
});
```
</Tab>
<Tab title="Python">
```python
from mcp.server.fastmcp import FastMCP
mcp = FastMCP("example-server")
@mcp.tool(
annotations={
"title": "Calculate Sum",
"readOnlyHint": True,
"openWorldHint": False
}
)
async def calculate_sum(a: float, b: float) -> str:
"""Add two numbers together.
Args:
a: First number to add
b: Second number to add
"""
result = a + b
return str(result)
```
</Tab>
</Tabs>
### Best practices for tool annotations
1. **Be accurate about side effects**: Clearly indicate whether a tool modifies its environment and whether those modifications are destructive.
2. **Use descriptive titles**: Provide human-friendly titles that clearly describe the tool's purpose.
3. **Indicate idempotency properly**: Mark tools as idempotent only if repeated calls with the same arguments truly have no additional effect.
4. **Set appropriate open/closed world hints**: Indicate whether a tool interacts with a closed system (like a database) or an open system (like the web).
5. **Remember annotations are hints**: All properties in ToolAnnotations are hints and not guaranteed to provide a faithful description of tool behavior. Clients should never make security-critical decisions based solely on annotations.
## Testing tools
A comprehensive testing strategy for MCP tools should cover:
* **Functional testing**: Verify tools execute correctly with valid inputs and handle invalid inputs appropriately
* **Integration testing**: Test tool interaction with external systems using both real and mocked dependencies
* **Security testing**: Validate authentication, authorization, input sanitization, and rate limiting
* **Performance testing**: Check behavior under load, timeout handling, and resource cleanup
* **Error handling**: Ensure tools properly report errors through the MCP protocol and clean up resources

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# Examples
This folder contains example skills that demonstrate what's possible with Claude's skills system. These examples range from creative applications (art, music, design) to technical tasks (testing web apps, MCP server generation) to enterprise workflows (communications, branding, etc.).
Each skill is self-contained in its own folder with a `SKILL.md` file containing the instructions and metadata that Claude uses. Browse through these examples to get inspiration for your own skills or to understand different patterns and approaches.
Many of the example skills are open source (Apache 2.0). We've also included the document creation & editing skills that power [Claude's document capabilities](https://www.anthropic.com/news/create-files) under the hood in the [`docx`](./docx), [`pdf`](./pdf), [`pptx`](./pptx), and [`xlsx`](./xlsx) subfolders. These are source-available, not open source, but we wanted to share these with developers as a reference for more complex skills that are actively used in a production AI application.
**Note:** These are reference examples for inspiration and learning. They showcase general-purpose capabilities rather than organization-specific workflows or sensitive content.
## Disclaimer
**These skills are provided for demonstration and educational purposes only.** While some of these capabilities may be available in Claude, the implementations and behaviors you receive from Claude may differ from what is shown in these examples. These examples are meant to illustrate patterns and possibilities. Always test skills thoroughly in your own environment before relying on them for critical tasks.
# Example Skills
This folder includes a diverse collection of example skills demonstrating different capabilities:
## Creative & Design
- **algorithmic-art** - Create generative art using p5.js with seeded randomness, flow fields, and particle systems
- **canvas-design** - Design beautiful visual art in .png and .pdf formats using design philosophies
- **slack-gif-creator** - Create animated GIFs optimized for Slack's size constraints
## Development & Technical
- **artifacts-builder** - Build complex claude.ai HTML artifacts using React, Tailwind CSS, and shadcn/ui components
- **mcp-server** - Guide for creating high-quality MCP servers to integrate external APIs and services
- **webapp-testing** - Test local web applications using Playwright for UI verification and debugging
## Enterprise & Communication
- **brand-guidelines** - Apply Anthropic's official brand colors and typography to artifacts
- **internal-comms** - Write internal communications like status reports, newsletters, and FAQs
- **theme-factory** - Style artifacts with 10 pre-set professional themes or generate custom themes on-the-fly
## Meta Skills
- **skill-creator** - Guide for creating effective skills that extend Claude's capabilities
- **template-skill** - A basic template to use as a starting point for new skills
# Document Skills
The [`docx`](./docx), [`pdf`](./pdf), [`pptx`](./pptx), and [`xlsx`](./xlsx) subfolders contain skills that Anthropic developed to help Claude create various document file formats. These skills demonstrate advanced patterns for working with complex file formats and binary data:
- **docx** - Create, edit, and analyze Word documents with support for tracked changes, comments, formatting preservation, and text extraction
- **pdf** - Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms
- **pptx** - Create, edit, and analyze PowerPoint presentations with support for layouts, templates, charts, and automated slide generation
- **xlsx** - Create, edit, and analyze Excel spreadsheets with support for formulas, formatting, data analysis, and visualization
**Important Disclaimer:** These document skills are point-in-time snapshots and are not actively maintained or updated. Versions of these skills ship pre-included with Claude. They are primarily intended as reference examples to illustrate how Anthropic approaches developing more complex skills that work with binary file formats and document structures.
# Try in Claude Code, Claude.ai, and the API
## Claude Code
You can register this repository as a Claude Code Plugin marketplace by running the following command in Claude Code:
```
/plugin marketplace add anthropics/skills
```
Then, to install a specific set of skills:
1. Select `Browse and install plugins`
2. Select `anthropic-agent-skills`
3. Select `document-skills` or `example-skills`
4. Select `Install now`
Alternatively, directly install either Plugin via:
```
/plugin install document-skills@anthropic-agent-skills
/plugin install example-skills@anthropic-agent-skills
```
After installing the plugin, you can use the skill by just mentioning it. For instance, if you install the `document-skills` plugin from the marketplace, you can ask Claude Code to do something like: "Use the PDF skill to extract the form fields from `path/to/some-file.pdf`"
## Claude.ai
These example skills are all already available to paid plans in Claude.ai.

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