"Cargo Doc" matching MCP servers:

Provides a documentation search MCP tool (search_docs) that enables AI agents to retrieve relevant chunks from BDC documentation using semantic embeddings and keyword search, with filtering by document type and date.

Enables searching and retrieving documents from a local folder to ground LLM answers in your files.

Self-hosted Go MCP server that crawls documentation sites into local Markdown/JSONL corpora and lets agents read pages, run crawls, check freshness, and diff changes with zero network access at read time. Single static binary, no CGO, Apache-2.0.

An MCP server that provides AI assistants with real-time access to Inductive Automation Ignition documentation, enabling accurate answers on Ignition-specific topics by searching live docs and fetching full pages.

MCP server that gives AI assistants direct access to live AVEVA PI System documentation, eliminating hallucination on PI-specific topics by fetching real answers from the official docs.

DocOrbit is an agent-native documentation intelligence layer that discovers, versions, indexes, retrieves, and verifies software documentation for coding agents. It provides 14 native MCP tools for AST-based doc retrieval, OpenAPI inspection, version pinning, and code verification.

MCP server for hybrid documentation search (keyword + vector) and RAG chat, enabling natural language queries with cited answers from indexed repositories.

Provides local technical documentation with hybrid search (semantic + BM25) for AI agents, ensuring access to up-to-date framework docs.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Turns any folder of PDFs, markdown, and text files into a local, queryable knowledge base exposed as an MCP server. Enables MCP-compatible agents to semantically search indexed documents, retrieve relevant passages with source and relevance scores, list or reindex documents, and inspect cache and token usage — instead of reading whole files into context.

Enables semantic and keyword search of Ceph documentation with version-aware, component-scoped indices, supporting command lookup and code example retrieval.

A local-first semantic search server for documents, supporting PDFs, Office files, and text/markdown, enabling natural language search via the Model Context Protocol (MCP).

Indexes your repo's markdown into a canonical doc store, serving agents the single current doc per question via MCP to save tokens and keep all agents on the same source of truth.

Enables MCP clients to search documents stored in OpenSQL/PostgreSQL using vector similarity, with support for version history and changelog retrieval.

Enables MCP clients to locally search, retrieve, and summarize project documentation using Ollama models, without cloud usage, while managing requests through a queue and optional model prewarming.

Enables AI to efficiently analyze and extract structured data from complex documents, especially Excel files, by providing tools like section reading and field mapping to reduce token usage and improve success rates.

An MCP server that integrates Dify knowledge bases, enabling AI assistants to retrieve and search content from Dify via tools like list datasets, get dataset details, and knowledge retrieval.

An MCP server that exposes grounded, source-attributed question-answering over a collection of PDF documents.

Enables semantic search and AI-powered Q&A over ingested GitHub documentation repositories via MCP tools.

Enables MCP-based access to Adhoc documentation, providing search, content retrieval, and feedback issue creation with audience gating and leak protection.