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

In-memory vector store with TF-IDF vectorization and cosine similarity search, paid per call via x402 micropayments.

An MCP server that enables AI clients to autonomously discover, analyze, fix, test, submit, and track open-source contributions on GitHub through specialized tools.

A comprehensive Model Context Protocol server providing 33 specialized research and search tools for Claude Desktop, enabling powerful search capabilities across academic, technical, and general domains.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Enables AI agents to search, watch, summarize, clip, and extract transcripts from YouTube videos, all without needing an API key or leaving the chat.

Fill standard legal agreement templates (NDAs, SAFEs, NVCA docs, employment, cloud terms) and produce DOCX files.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

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

An MCP server that enables AI assistants to navigate, search, and analyze local Keycloak source code to support developer customizations like SPIs and authenticators. It provides tools for searching classes, generating boilerplate code, detecting breaking changes between versions, and tracing dependencies.

An open-source Model Context Protocol application management platform that allows users to create applications from GitHub repositories with automatic information extraction and database integration.

Gives multiple AI coding agents a shared, persistent memory by indexing your code and documentation into a vector database with AST-aware chunking and hybrid semantic/keyword search. Agents can search across projects and store, update, or forget decisions, conventions and lessons learned, all self-hosted with local embeddings.

An MCP server that builds structured research source packs for a topic, extracting verified facts, quotes, numbers, dates, and primary links with a coverage map of claims across sources.

Enables AI agents to semantically search GitHub repository documentation by automatically fetching, vectorizing, and indexing content into an Upstash Vector database. It provides a standard MCP interface for agents to retrieve relevant documentation snippets through natural language queries.

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.

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.

Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs

Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.

A private, open-source AI-text checker. Get a read on whether text looks AI-written, the exact AI-tell spans to fix, a reuse check, and a grammar pass.

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