"An open-source vector database for similarity search and AI applications" matching MCP servers:

Enables researching, verifying, comparing, and composing open-source AI projects with transparent evidence and uncertainty boundaries through read-only tools.

A CLI-first semantic code search tool with MCP integration for AI assistants, enabling semantic search, AST-aware parsing, and code analysis across 13 languages.

Combines Neo4j graph database with vector search using OpenAI embeddings for intelligent semantic search across knowledge graphs.

Web search, page fetching, and research from the terminal or any MCP client — no API key required.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

Integrates RAG into AI agents via MCP Server, supporting multiple vector database technologies for collection management and search operations.

Provides agent-friendly web search via MCP with zero-config free engines, region-aware failover, freshness filtering, and a one-call research tool that searches, fetches, and summarizes pages.

Enables AI agents to discover and access 800TB+ of public geospatial data from Source Cooperative, with tools for listing organizations, products, files, and fuzzy search.

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

MCP server for searching, browsing, and analyzing decompiled Minecraft source code locally. Supports symbol lookup, text search, reference lookup, and lightweight RAG.

Enables a local, read-only search over user-provided tabletop campaign source cards and module directories, routing queries to ranked hits across Markdown, JSON, and YAML text files while excluding core rulebook and SRD content by default. Returns file-and-line pointers with small context windows, plus explicit private-source opt-in, so a game master can locate and open the exact passage in their own library.

Provides intelligent search aggregation for AI agents, automatically detecting intent and returning structured results with links to platforms for various categories like movies, books, products, courses, and more.

Enables semantic and full-text search over markdown notes, with tools to create, edit, move, and delete notes, all through MCP. Runs entirely locally using Ollama for embeddings and SQLite for storage, working with Obsidian or standalone.

Enables agents to turn documents into vectors, perform approximate nearest neighbor search with HNSW, and filter by metadata via MCP tools for RAG workflows.

Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.

A clean architecture backend API that registers and semantically searches data using vector embeddings, acting as an MCP context provider to connect AI models to external data.

Provides Vertex AI Search for Commerce product search as a tool, enabling AI agents to search product catalogs using natural language queries.

Enables querying a unified database of items from Gmail, Notion, Linear, and Google Calendar through MCP tools, including filtered lookups, stats, and natural-language questions.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.