"DOI" matching MCP servers:

Enables agents to search, retrieve, and list open-licensed documents with verifiable provenance, attaching sha256, DOI, and OpenTimestamps proof to every response.

Ground Claude, ChatGPT, Cursor, and Windsurf in 300M scientific works — every citation a verifiable DOI.

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.

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 real-time web search with source citations by leveraging Perplexity AI's Sonar models through SAP AI Core. It integrates with Claude Code to provide deep analysis, reasoning, and up-to-date information from the web.

Enhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.

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

Provides programmatic access to UK legal documents with hybrid semantic search and Model Context Protocol integration for AI assistants.

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 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 intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.

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.