A
licenseNot graded
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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"Ways to collect or retrieve emails" matching MCP servers:
- FlicenseNot gradedqualityCmaintenanceMCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.
- 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
- AlicenseAqualityCmaintenanceEnables LLM hosts to retrieve live, relevant documentation excerpts from official library docs sites via a search-and-RAG tool, avoiding reliance on training data.1MIT
- 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
- FlicenseAqualityDmaintenanceAn MCP server for semantic search and retrieval of indexed Slack messages stored in Qdrant using Cohere reranking via AWS Bedrock. It enables users to search through Slack history, retrieve full message threads, and access channel or user statistics through natural language.5
- 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
- FlicenseAqualityBmaintenanceSemantic search over project-specific decision rules using Chroma, enabling LLMs to retrieve relevant context.1
- AlicenseAqualityCmaintenanceAn MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.2Apache 2.0
- 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).396MIT
- 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- FlicenseCqualityDmaintenanceA Model Context Protocol server that enables users to perform third-party enrichment lookups for security observables (IP addresses, domains, URLs, emails) through services like VirusTotal, Shodan, and others.15
@manasdb/mcp-serverofficial
AlicenseNot gradedqualityDmaintenanceProvides 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.15MIT- AlicenseNot gradedqualityCmaintenanceEnables 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
- AlicenseNot gradedqualityCmaintenanceHelps developers tackle legacy codebases by giving AI coding assistants context through Qdrant vector store and Agentic RAG with Ollama or DeepSeek.11513MIT