dodopayments/contextmcp

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šŸ“‡ ā˜ļø šŸ  - Self-hosted MCP server that indexes documentation from various sources and serves it to AI Agents with semantic search.

Quick Install

One-Click IDE Configuration
claude_desktop_config.json
{
  "mcpServers": {
    "dodopayments-contextmcp": {
      "command": "npx",
      "args": [
        "-y",
        "dodopayments-contextmcp"
      ]
    }
  }
}
Or

Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.

Documentation Overview

ContextMCP

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

Packages

PackageDescriptionPublished
packages/cliCLI scaffolding toolāœ… 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.

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Last checked: 7/28/2026, 10:17:01 PM

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