A
license-
qualityD
maintenanceEnables semantic search across multiple Qdrant vector database collections, supporting multi-query capability and providing semantically relevant document retrieval with configurable result counts.
46
MIT
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"Methods to Retrieve Website Content" matching MCP servers:
- AlicenseDqualityCmaintenanceA lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.12MIT
- AlicenseAqualityCmaintenanceEnables semantic search and analysis of customer support tickets. Provides tools to search tickets, analyze the dataset, and retrieve individual tickets using natural language.3MIT
- AlicenseAqualityBmaintenanceEnables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.4AGPL 3.0
- AlicenseAqualityDmaintenanceA Model Context Protocol (MCP) server that provides a local-first RAG engine for your markdown documents. It uses a file-based Milvus vector database to index your notes, enabling LLMs to perform semantic search and retrieve relevant content from your local files.355Apache 2.0
Chroma MCP Serverofficial
AlicenseAqualityDmaintenanceA server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.13584Apache 2.0- AlicenseAqualityCmaintenanceA Model Context Protocol server for Chroma, enabling AI models to create collections and retrieve data using vector search, full text search, and metadata filtering.13Apache 2.0
- AlicenseAqualityDmaintenanceAn experimental MCP server that makes YouTube playlist transcripts available for AI assistants, enabling search and conversation about video content.13Apache 2.0
- FlicenseAqualityBmaintenanceSemantic search over project-specific decision rules using Chroma, enabling LLMs to retrieve relevant context.1
- AlicenseAqualityCmaintenanceCline MCP integration that allows users to save, search, and format memories with semantic understanding, providing tools to store and retrieve information using vector embeddings for meaning-based search.129MIT
- AlicenseAqualityDmaintenanceEnables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).3106MIT
- FlicenseBqualityDmaintenanceA Model Context Protocol server that enables semantic vector search over Obsidian notes, allowing AI assistants to intelligently search and retrieve relevant note content.12
- FlicenseBqualityDmaintenanceEnables GitHub Copilot to query local ChromaDB instances to retrieve relevant documents and context for AI conversations. It allows users to search vector collections using natural language tools directly within VS Code.1
- FlicenseBqualityDmaintenanceEnhances large language models with competitive programming knowledge by leveraging OI-Wiki content through vector search, allowing models to retrieve relevant algorithms and techniques.124
LanceDB MCP Serverofficial
FlicenseBqualityDmaintenanceA basic serverless MCP server using LanceDB to store and retrieve documents via three tools: ingest, retrieve, and get table details.325- AlicenseBqualityDmaintenanceEnables fetching relevant content and embeddings from Supavec via the Model Context Protocol, allowing AI assistants like Claude to access vector search capabilities.274MIT
- AlicenseBqualityDmaintenanceEnables retrieval-augmented generation by embedding queries with a chosen provider (e.g., OpenAI) and searching supported vector stores (Pinecone, pgvector) to return relevant content.1Apache 2.0
@manasdb/mcp-serverofficial
Alicense-qualityDmaintenanceProvides a plug-and-play persistent memory layer for MCP-compatible AI assistants, enabling them to store, retrieve, and delete memories across multiple databases simultaneously using semantic vector search.5MIT- Alicense-qualityCmaintenanceEnables AI assistants to save, retrieve, and manage research content using ChromaDB vector storage with semantic search, topic organization, and automatic deduplication powered by OpenAI embeddings.MIT
- Alicense-qualityDmaintenanceEnables robots to store, retrieve, and consolidate episodic experiences including physical parameters, trajectories, and outcomes. It supports hybrid vector search with structured filtering and spatial sorting to help robotic agents learn from past successes and failures.28Apache 2.0