How does docs-mcp-server MCP Server index documentation?
It scrapes content from specified URLs, splits it into meaningful chunks, and stores it in a SQLite database using FTS5 for full-text search. Vector embeddings are currently disabled.
@xinlei413
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"DOC-Server-MCP": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"\\"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
docs-mcp-server MCP Server is a Model Context Protocol server that fetches, indexes, and searches third-party package documentation. It scrapes content from websites, GitHub, npm, PyPI, or local files, and stores it in a SQLite database with full-text search. It also integrates with OpenRouter API for large language model chat/completions.
Run the server via Docker (recommended) or npx, configured in your MCP client settings (e.g., Claude, Cline, Roo). Set the required OPENAI_API_KEY environment variable and optionally configure embedding models. The server exposes MCP tools for scraping, searching, and managing documentation. Use the CLI to manage the index directly.
It scrapes content from specified URLs, splits it into meaningful chunks, and stores it in a SQLite database using FTS5 for full-text search. Vector embeddings are currently disabled.
OpenAI, Google Vertex AI, Google Generative AI (Gemini), AWS Bedrock, and Azure OpenAI are supported via environment variables. However, embedding functionality is currently disabled and will throw errors.
Yes, use npx: `npx -y --package=@arabold/docs-mcp-server docs-server`. Node.js must be installed, and the same method should be used for the CLI.
`OPENAI_API_KEY` is required. Additional variables depend on the embedding provider (e.g., `AZURE_OPENAI_API_KEY`, `AWS_ACCESS_KEY_ID`, etc.). For OpenRouter chat, set `OPENAI_API_BASE` to the OpenRouter endpoint.
Yes, it supports storing and querying documentation for different library versions, including unversioned content, with distinct search capabilities.

Personal context for every AI: search, read, and write back to your private Markdown library of articles, threads, PDFs, notes, and captured ChatGPT/Claude/Gemini/Grok conversations. Remote server, OAuth 2.1 paste-and-au

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