$ loading_
Index docs from websites, repos, and folders for AI search and retrieval.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "docs-mcp-server" yet — see the docs or source repo.
Index this Git repository, the project documentation website, and my local README folder, and let me query API usage, installation steps, and configuration examples through search and fetch.
A unified documentation index for AI use, enabling cross-source search and returning relevant excerpts or original content.
Connect our internal docs site, DevOps repository, and local runbooks so I can quickly search deployment workflows, troubleshooting steps, and environment variable details.
Search results organized by source, allowing the AI to quickly locate relevant docs and extract key guidance.
Index multiple product documentation sites and local reference folders so the AI can search feature descriptions, version differences, and supporting materials, and cite the relevant docs in its answers.
A searchable knowledge base that improves answer accuracy and lets the AI ground responses in matched documentation.
Search and manage technical docs in your IDE with natural language.
Search official library docs and return clean text ready for LLM use.
Make any MkDocs documentation site searchable and explorable from MCP clients.
Fetch and parse llms.txt docs for dynamic AI documentation search and Q&A.
Access GitHub repositories and docs via API with search and content decoding.
Scrape web content and search documentation through a FastMCP-powered MCP server.