"General Documentation Search" matching MCP servers:

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

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

Provides semantic search capabilities over PyTorch documentation, enabling users to find relevant documentation, APIs, code examples, and error messages through Claude Code integration.

Enables AI assistants to fetch, index, and perform semantic RAG-based searches on API documentation from various sources. It provides tools for hybrid search and collection management, allowing users to access up-to-date documentation from projects like Gemini and FastMCP.

Enables AI agents to search and query documentation from git repositories using hybrid search and structured metadata queries.

Enables semantic search and retrieval over a locally supplied copy of Lemma's documentation, providing ranked excerpts and full-text chunk access via read-only MCP tools without calling live banking APIs.

Provides fast, token-efficient search over coding agent documentation (e.g., Claude Code, Cursor) using local SQLite FTS5 indexing, with tools for searching snippets, reading pages, and grepping markdown.

Indexes your project's markdown documentation and exposes it to AI agents via local hybrid search (lexical + semantic) with progressive disclosure tools.

Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.

Enables agents to perform full-text search and read Hermes Agent documentation offline from a local cache, without scraping the site.

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.

Versioned library documentation retrieval MCP server for coding agents, providing accurate, versioned, and traceable API documentation snippets with scoring, caching, and offline support.

Provides AI agents with 12 real-time tools for search synthesis, grounded research dossiers, claim verification, citation generation, sentiment analysis, expert ranking, timeline creation, and competitive landscape mapping over Streamable HTTP or stdio.

MCP server for Doubao Search that enables real web search in any MCP client, backed by ByteDance-exclusive Chinese sources and the open web.

Enables natural-language search, page reading, deployment configuration, and build-log diagnosis over Liara cloud documentation, with a bundled corpus and no database or API key required.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

A server that provides AI agents with full OpenClaw documentation via BM25 search, enabling them to look up configurations, providers, and other topics without web lookups.

MCP server for the Point Knowledge API that enables AI coding assistants to search and retrieve curated technical documentation (RFCs, framework docs, etc.) with hybrid search and precise citations.

Enables Claude to search and read documentation, ask RAG AI questions (one-shot or in a conversation), and create/edit documents in the Meet Rupert knowledgebase, including handling image attachments.

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

Enables semantic search over ByJG's documentation, letting LLMs answer questions about ByJG libraries and cite the pages where answers were found.

Provides semantic search over AWS Cloudscape Design System documentation using natural language queries, enabling AI assistants to efficiently find and retrieve component documentation with token-efficient responses.

MCP server for semantic search across llms.txt documentation sources, with hybrid two-stage retrieval and automatic background refresh.

Enables LLMs to search Couchbase documentation through MCP and retrieve natural-language answers with source links.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

Enables natural-language semantic search over your own local files through an MCP server, fully offline without API keys or a server daemon, with optional LLM-grounded answers and exact file:line sources.

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

Connect AI assistants to Manticore Search. Execute SQL queries, list tables, get schemas, and fetch documentation. Perfect for building RAG applications and search-powered AI agents.