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Context MCP

Community Search and web

Self-hosted documentation indexer that serves docs from various sources to agents with semantic search.

Source code Documentation

Install

The installation steps are in the documentation below. Documentation

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. ContextMCP
  2. Quick Start
  3. What is ContextMCP?
  4. Ecosystem
  5. Repository Structure
  6. Packages
  7. Development
  8. Documentation
  9. Contributing
  10. License

ContextMCP

Self-hosted MCP server for your documentation. Index your documentation from across the sources and serve it via the Model Context Protocol (MCP) and REST API.

Quick Start

# Scaffold a new project
npx contextmcp init my-docs-mcp

# Follow the prompts, then:
cd my-docs-mcp
npm install

# Configure your API keys
cp .env.example .env
# Edit .env with your PINECONE_API_KEY and an embedding provider key
# (OPENAI_API_KEY for provider: openai, or GEMINI_API_KEY for provider: gemini)

# Configure your documentation sources
# Edit config.yaml

# Index your documentation
npm run reindex

# Edit the cloudflare-worker
# Deploy the MCP server
cd cloudflare-worker
npm install
npm run deploy

What is ContextMCP?

ContextMCP creates a searchable knowledge base from your documentation that AI assistants can query via the Model Context Protocol (MCP).

Supported Content Types
ParserContent TypesExamples
mdxMDX/JSX documentationMintlify, Fumadocs, Docusaurus
markdownPlain Markdown filesREADMEs, CHANGELOGs
openapiOpenAPI/Swagger specsAPI reference docs
How It Works
  1. Parse - Extract content from your docs, APIs, and READMEs
  2. Chunk - Split into semantic chunks optimized for search
  3. Embed - Generate embeddings using OpenAI or Gemini
  4. Store - Upload to Pinecone vector database
  5. Search - Query via MCP from AI assistants

Ecosystem

Add a chat UI with ContextChat

ContextMCP serves retrieval; pair it with **ContextChat** to give your docs a drop-in, embeddable "Ask AI" widget. ContextChat is a single Cloudflare Worker that queries your ContextMCP /search endpoint and streams answers with inline citations — add it to any site or docs page with one <script> tag.

Repository Structure

contextmcp/
├── packages/
│   ├── cli/              # npx contextmcp (npm package)
│   ├── template/         # Project template (scaffolded to users)
│   └── website/          # contextmcp.ai documentation site
└── deployments/
    └── dodopayments/     # Dodo Payments specific deployment

Packages

PackageDescriptionPublished
packages/cliCLI scaffolding tool✅ npm: contextmcp
packages/templateProject template(copied by CLI)
packages/websiteDocumentation site(deployed to Vercel)

Development

Prerequisites
  • Node.js 18+
Setup
# Install all dependencies
npm install

# Development
npm run dev:website     # Run website locally
npm run dev:cli         # Watch CLI for changes

# Build
npm run build:website   # Build website
npm run build:cli       # Build CLI

# Type checking
npm run typecheck       # Check all packages

Documentation

Visit contextmcp.ai/docs for full documentation.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines on how to contribute to this project.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Frequently asked questions

What is Context MCP?

Self-hosted documentation indexer that serves docs from various sources to agents with semantic search.

How do I install Context MCP?

Follow the installation steps in its documentation, shown on this page and in its repository.

Is Context MCP open source?

Yes. Its code is on GitHub under the Apache-2.0 license.

Who maintains Context MCP?

It is published by dodopayments. AI.tn lists it but does not maintain or endorse it.

From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.