A
license-
qualityD
maintenanceA server that enables Claude AI to interact with Weaviate vector databases, supporting both search and storage operations through Anthropic's MCP protocol.
Last updated
2
GPL 3.0
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"Using a localhost API for development" matching MCP servers:
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- Flicense-quality-maintenanceA local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.Last updated
- Alicense-qualityDmaintenanceA local-first Graph-RAG system combining ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q&A over Obsidian vaults, supporting MCP clients like Claude Desktop, Cursor, and Raycast.Last updatedMIT
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- AlicenseAqualityAmaintenanceA persistent semantic memory system for Claude Code, using vector search and a judgment ledger to surface prior decisions and calibrate predictions.Last updated17MIT
- 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.Last updated13Apache 2.0
- AlicenseBqualityDmaintenanceProvides persistent knowledge graph memory for AI agents with local semantic search using Neo4j and ONNX embeddings, enabling offline operation with zero API costs.Last updated1728MIT
@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.Last updated33MIT
tigergraph-mcpofficial
Alicense-qualityBmaintenanceModel Context Protocol (MCP) server for TigerGraph that lets AI agents interact with TigerGraph through the MCP standard using pyTigerGraph's async APIs.Last updated3Apache 2.0- Alicense-qualityFmaintenanceProvides persistent, semantic memory storage for LLMs across sessions using vector embeddings and FAISS search. Features bio-inspired memory consolidation, intelligent forgetting, and semantic retrieval without API costs.Last updatedMIT
- Alicense-qualityAmaintenanceMCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.Last updatedMIT
- Alicense-qualityAmaintenanceA high-performance MCP server for semantic search and codebase indexing using the Qdrant vector database. It features optimized embedding pipelines, AST-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search.Last updated30210MIT
- Alicense-quality-maintenanceProvides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.Last updated
- Alicense-quality-maintenanceA Python server that enables retrieval-augmented generation through semantic, question/answer, and style search modalities using PostgreSQL and pgvector for embedding storage and retrieval.Last updated2Apache 2.0
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