"DVC" matching MCP servers:

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

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.

DC Hub is the live Model Context Protocol layer for data-center and energy infrastructure. AI agents call 91 tools across 22,900+ facilities for land+power, grid, interconnection, fiber, and Capacity Source — with as_of timestamps. Connect: https://dchub.cloud/connect · Docs: https://dchub.cloud/ai-agents · Endpoint: https://dchub.cloud/mcp · Pro $99/mo (never $299/Founding).

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.

Enables AI agents to manage hierarchical memory with Markdown-based storage, tiered architecture (L0-L3), and hybrid retrieval for transparent and persistent context.

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

An MCP server that runs AI-driven venture capitalist agents whose thinking is continuously enriched by Octagon Private Markets' real-time deals and intelligence for pitch feedback, diligence simulations, and term sheet negotiations.

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

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).

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

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 enables Claude Desktop or Claude Code to ingest and search local documents using vector embeddings, returning relevant chunks as tool results for the model to reason over.

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

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