Context7 Docs

Context7 Documentation Fetcher

Overview

Fetch up-to-date documentation and code examples for any library using Context7's HTTP API. This skill replicates Context7 MCP functionality with token-efficient progressive disclosure.

When to Use This Skill

This skill should be the FIRST choice for library/framework documentation.

Trigger patterns:

• User asks for documentation: "get me the React docs", "show me Next.js docs"
• User needs API references: "how do I use X API", "what's the syntax for Y"
• User wants setup instructions: "how to install Z", "configure W"
• Code generation tasks: Before writing code for a library, fetch its docs first
• User mentions library names: "help with FastAPI", "using Tailwind"
• Troubleshooting with libraries: When fixing bugs or errors related to specific libraries

Benefits over WebFetch/WebSearch:

• Curated, current documentation from official sources
• Structured format optimized for code generation
• Topic filtering for focused results
• Version-specific documentation when needed

Setup

API Key Required: Set CONTEXT7_API_KEY environment variable. Get key from https://context7.com/dashboard

export CONTEXT7_API_KEY="your-api-key"

Quick Start

Two-Step Workflow

1. Search for library to get Context7-compatible ID
2. Fetch documentation using that ID

Exception: Skip search if user provides exact ID format (/org/project or /org/project/version)

Searching for Libraries

Use scripts/context7_client.py search to resolve library names to Context7 IDs.

Basic search:

python scripts/context7_client.py search "React"

Output format:

Found 3 results for 'React':

1. React
   ID: /facebook/react
   Description: JavaScript library for building user interfaces

2. React Router
   ID: /remix-run/react-router
   Description: Declarative routing for React

Selection criteria:

• Exact name matches prioritized
• Description relevance to query intent
• Documentation coverage (higher code snippet count)
• Source reputation (High/Medium preferred)

Common patterns:

# Framework search
python scripts/context7_client.py search "Next.js"
# Returns: /vercel/next.js

# Database client
python scripts/context7_client.py search "MongoDB"
# Returns: /mongodb/docs

# UI library
python scripts/context7_client.py search "shadcn"
# Returns: /shadcn/ui

Fetching Documentation

Use scripts/context7_client.py docs with resolved library ID.

Basic fetch:

python scripts/context7_client.py docs vercel/next.js

With topic filter:

python scripts/context7_client.py docs vercel/next.js --topic routing

With token limit:

python scripts/context7_client.py docs vercel/next.js --tokens 3000

Specific version:

python scripts/context7_client.py docs vercel/next.js/v15.1.8

Combined parameters:

python scripts/context7_client.py docs vercel/next.js --topic "app router" --tokens 2000

Parameters

Library ID Format

• Standard: /org/project (e.g., /vercel/next.js)
• Versioned: /org/project/version (e.g., /vercel/next.js/v15.1.8)
• Leading slash optional: Script handles both vercel/next.js and /vercel/next.js

Optional Filters

• --topic: Focus on specific subject (e.g., "routing", "hooks", "authentication")
• --tokens: Limit documentation size (default: 5000)
  • Use lower values (1000-2000) for focused queries
  • Use higher values (5000-10000) for comprehensive references

Output Formats

• Default: Formatted markdown documentation
• --json: Raw JSON for programmatic parsing

Error Handling

Common errors:

1. "Context7 API key required"

   • Set CONTEXT7_API_KEY environment variable

2. "Authentication failed"

   • Verify API key is correct
   • Check key hasn't been revoked

3. "Library not found"

   • Verify library ID is correct
   • Try searching first to confirm ID

4. "Rate limited. Retry after X seconds"

   • Wait specified duration
   • Consider implementing exponential backoff

5. Network errors

   • Check internet connectivity
   • Verify Context7 API is accessible

Usage Examples

Example 1: Next.js App Router documentation

# Search for Next.js
python scripts/context7_client.py search "Next.js"

# Fetch App Router docs
python scripts/context7_client.py docs vercel/next.js --topic "app router"

Example 2: React hooks with token limit

# Direct fetch (known ID)
python scripts/context7_client.py docs facebook/react --topic hooks --tokens 2000

Example 3: Specific library version

# Search for library
python scripts/context7_client.py search "Tailwind CSS"

# Fetch specific version docs
python scripts/context7_client.py docs tailwindlabs/tailwindcss/v3.4.0

Integration Tips

For code generation

1. Search for library if ID unknown
2. Fetch docs with relevant topic filter
3. Use documentation to generate accurate, up-to-date code
4. Consider token limits based on scope

For setup/configuration

1. Fetch docs without topic filter for comprehensive guide
2. Use higher token limit (5000+) for full instructions
3. Look for "getting started" or "installation" sections

For API references

1. Use topic filter for specific API sections
2. Moderate token limits (2000-3000) for focused references
3. Fetch multiple topics separately if needed

Token Efficiency

Progressive disclosure vs MCP:

• MCP: All tools always in context (~2k tokens)
• This skill:
  • Metadata: ~100 words (always)
  • SKILL.md: <5k words (when triggered)
  • Scripts: Executed without loading to context
  • References: Loaded only when needed

Best practices:

• Use topic filters to get focused docs
• Adjust token limits based on query scope
• Cache results when appropriate
• Only invoke skill when documentation is actually needed

Resources

scripts/context7_client.py

Python client for Context7 API with CLI interface. Handles authentication, search, and documentation fetching. Can be executed directly without loading to context.

references/api_details.md

Detailed API reference including endpoints, authentication, rate limits, and error codes. Load into context if deeper API understanding is needed for debugging or advanced usage.