Context7 Efficient Documentation Fetcher
SkillDocs & knowledgeToken-efficient library API documentation fetcher using Context7 MCP with 77% token savings. Fetches code examples, API references, and usage patterns for published libraries (React, Next.js, Prisma, etc). Use when users ask "how do I use X library", need code examples, want API syntax, or are learning a framework's official API. Triggers: "Show me React hooks", "Prisma query syntax", "Next.js routing API". NOT for exploring repo internals/source code (use researching-with-deepwiki) or local files.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Context7 Efficient Documentation Fetcher skill
What this skill tells your AI
The instructions your AI receives, as published by mjunaidca/mjs-agent-skills in .claude/skills/fetching-library-docs/SKILL.md and read by ahel’s review.
Fetch library documentation with automatic 77% token reduction via shell pipeline.
Quick Start
Always use the token-efficient shell pipeline:
# Automatic library resolution + filtering
bash scripts/fetch-docs.sh --library <library-name> --topic <topic>
# Examples:
bash scripts/fetch-docs.sh --library react --topic useState
bash scripts/fetch-docs.sh --library nextjs --topic routing
bash scripts/fetch-docs.sh --library prisma --topic queries
Result: Returns ~205 tokens instead of ~934 tokens (77% savings).
Standard Workflow
For any documentation request, follow this workflow:
1. Identify Library and Topic
Extract from user query:
- Library: React, Next.js, Prisma, Express, etc.
- Topic: Specific feature (hooks, routing, queries, etc.)
2. Fetch with Shell Pipeline
bash scripts/fetch-docs.sh --library <library> --topic <topic> --verbose
The --verbose flag shows token savings statistics.
3. Use Filtered Output
The script automatically:
- Fetches full documentation (934 tokens, stays in subprocess)
- Filters to code examples + API signatures + key notes
- Returns only essential content (205 tokens to Claude)
Parameters
Basic Usage
bash scripts/fetch-docs.sh [OPTIONS]
Required (pick one):
--library <name>- Library name (e.g., "react", "nextjs")--library-id <id>- Direct Context7 ID (faster, skips resolution)
Optional:
--topic <topic>- Specific feature to focus on--mode <code|info>- code for examples (default), info for concepts--page <1-10>- Pagination for more results--verbose- Show token savings statistics
Mode Selection
Code Mode (default): Returns code examples + API signatures
--mode code
Info Mode: Returns conceptual explanations + fewer examples
--mode info
Common Library IDs
Use --library-id for faster lookup (skips resolution):
React: /reactjs/react.dev
Next.js: /vercel/next.js
Express: /expressjs/express
Prisma: /prisma/docs
MongoDB: /mongodb/docs
Fastify: /fastify/fastify
NestJS: /nestjs/docs
Vue.js: /vuejs/docs
Svelte: /sveltejs/site
Workflow Patterns
Pattern 1: Quick Code Examples
User asks: "Show me React useState examples"
bash scripts/fetch-docs.sh --library react --topic useState --verbose
Returns: 5 code examples + API signatures + notes (~205 tokens)
Pattern 2: Learning New Library
User asks: "How do I get started with Prisma?"
# Step 1: Get overview
bash scripts/fetch-docs.sh --library prisma --topic "getting started" --mode info
# Step 2: Get code examples
bash scripts/fetch-docs.sh --library prisma --topic queries --mode code
Pattern 3: Specific Feature Lookup
User asks: "How does Next.js routing work?"
bash scripts/fetch-docs.sh --library-id /vercel/next.js --topic routing
Using --library-id is faster when you know the exact ID.
Pattern 4: Deep Exploration
User needs comprehensive information:
# Page 1: Basic examples
bash scripts/fetch-docs.sh --library react --topic hooks --page 1
# Page 2: Advanced patterns
bash scripts/fetch-docs.sh --library react --topic hooks --page 2
Token Efficiency
How it works:
fetch-docs.shcallsfetch-raw.sh(which usesmcp-client.py)- Full response (934 tokens) stays in subprocess memory
- Shell filters (awk/grep/sed) extract essentials (0 LLM tokens used)
- Returns filtered output (205 tokens) to Claude
Savings:
- Direct MCP: 934 tokens per query
- This approach: 205 tokens per query
- 77% reduction
Do NOT use mcp-client.py directly - it bypasses filtering and wastes tokens.
Advanced: Library Resolution
If library name fails, try variations:
# Try different formats
--library "next.js" # with dot
--library "nextjs" # without dot
--library "next" # short form
# Or search manually
bash scripts/fetch-docs.sh --library "your-library" --verbose
# Check output for suggested library IDs
Verification
Run: python3 scripts/verify.py
Expected: ✓ fetch-docs.sh ready
If Verification Fails
- Run diagnostic:
ls -la scripts/fetch-docs.sh - Check: Script exists and is executable
- Fix:
chmod +x scripts/fetch-docs.sh - Stop and report if still failing - do not proceed with downstream steps
Troubleshooting
| Issue | Solution |
|---|---|
| Library not found | Try name variations or use broader search term |
| No results | Use --mode info or broader topic |
| Need more examples | Increase page: --page 2 |
| Want full context | Use --mode info for explanations |
| Permission denied | Run: chmod +x scripts/*.sh |
References
For detailed Context7 MCP tool documentation, see:
- references/context7-tools.md - Complete tool reference
Implementation Notes
Components (for reference only, use fetch-docs.sh):
mcp-client.py- Universal MCP client (foundation)fetch-raw.sh- MCP wrapperextract-code-blocks.sh- Code example filter (awk)extract-signatures.sh- API signature filter (awk)extract-notes.sh- Important notes filter (grep)fetch-docs.sh- Main orchestrator (ALWAYS USE THIS)
Architecture: Shell pipeline processes documentation in subprocess, keeping full response out of Claude's context. Only filtered essentials enter the LLM context, achieving 77% token savings with 100% functionality preserved.
Signals
- GitHub stars
- 28
- Forks
- 12
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
fetching-library-docs- Source
- github.com/mjunaidca/mjs-agent-skills