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MCP verified MIT Self-run

Context7 ChatGPT Bridge

mcp-salah9003-context7-chatgpt-bridge · by salah9003

A bridge that allows ChatGPT to access up-to-date programming documentation through the Context7 MCP server. Implements ChatGPT's required search and fetch tools while using Context7's documentation database internally.

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Install

$ agentstack add mcp-salah9003-context7-chatgpt-bridge

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Context7 ChatGPT Bridge

Why This Exists

ChatGPT needs access to current programming documentation but requires specific search and fetch tools. Context7 provides excellent up-to-date docs but uses different tools (resolve-library-id and get-library-docs). This bridge translates between them, giving ChatGPT access to Context7's documentation database.

What It Does

A bridge that allows ChatGPT to access up-to-date programming documentation through the Context7 MCP server. Implements ChatGPT's required search and fetch tools while using Context7's documentation database internally.

Requirements

  • Node.js >= 18.0.0
  • Python >= 3.8
  • ngrok (for ChatGPT access)

Quick Start

  1. Install dependencies:

``bash pip install -r requirements.txt ``

  1. Start the bridge:

``bash python context7_bridge.py ``

The script automatically starts ngrok and displays the ChatGPT-ready URL.

  1. Add to ChatGPT:

Copy the displayed URL to ChatGPT's MCP connectors: `` https://abc123.ngrok-free.app/sse ``

Available Tools

search

Search for programming libraries and frameworks. Supports both library names (e.g., "React", "MongoDB") and direct Context7 library IDs (e.g., "/reactjs/react.dev").

fetch

Fetch comprehensive documentation for specific libraries. Supports advanced parameters:

  • Basic: library_id
  • Topic-focused: library_id|topic:hooks
  • Custom tokens: library_id|tokens:15000
  • Combined: library_id|topic:authentication|tokens:12000

Example Topics

  • hooks - React hooks, useEffect, useState
  • routing - Navigation, route setup
  • authentication - Login, security, JWT
  • installation - Setup, configuration
  • api - API reference, methods
  • examples - Code examples, tutorials

How It Works

ChatGPT → ngrok → Bridge → Context7 MCP Server → Documentation Database
  1. ChatGPT sends search/fetch requests to your bridge
  2. Bridge translates these to Context7's resolve-library-id/get-library-docs calls
  3. Context7 returns current documentation
  4. Bridge formats responses for ChatGPT

Configuration

Command-line options:

python context7_bridge.py --help
  • --port - Port to run on (default: 8000)
  • --host - Host to bind to (default: 127.0.0.1)
  • --no-ngrok - Disable automatic ngrok tunnel

Environment variables:

  • LOG_LEVEL - Logging level (default: INFO)

Manual Setup

If you prefer manual ngrok control:

# Start without ngrok
python context7_bridge.py --no-ngrok

# In another terminal
ngrok http 8000

Testing

Test without ChatGPT:

# Health check
curl http://localhost:8000/health

# Test search
curl -X POST http://localhost:8000/sse \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search","arguments":{"query":"react"}}}'

Troubleshooting

"Could not get response from Context7 server"

  • Ensure Node.js and npx are installed and in PATH

"Unknown document ID"

  • Always call search before fetch to get valid IDs
  • Or use direct Context7 library IDs (starting with /)
  • Note: Tool descriptions may need refinement for ChatGPT to better understand the search-first workflow - currently works but ChatGPT occasionally has hiccups with the sequence

Debug mode:

LOG_LEVEL=DEBUG python context7_bridge.py

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.