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    A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.
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    MIT
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    Official Telys MCP server: private, on-device AI memory and retrieval powered by native Mojo kernels. 19 tools: memory CRUD, semantic + BM25 search, single-key filters, compaction/IVF/tuning and self-refreshing repo auto-indexing. Stdio. Introspection needs no credentials; execution requires a one-time free telys login. Source: packages/telys-sdk/telys/mcp.py. Registry: io.github.thyn-ai/telys.
    19
    Apache 2.0
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    askDB is an MCP server that retrieves relevant database schema (DDL) from a Pinecone index and provides it to LLMs to write SQL, without connecting to the database itself.
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    A Byzantine fault-tolerant MCP Memory server that uses SQLite write-ahead logging and FAISS hybrid vector search for deterministic, secure memory operations.
    3
    Apache 2.0
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    Local-first, source-traceable memory for AI agents — no LLM at ingest, $0 per message, zero data egress. Gives Claude Code, Cursor, and any MCP client one shared persistent memory with semantic recall, belief revision, selective forgetting, and a provenance guard that blocks acting on stale or unconfirmed memories.
    23
    17 PyPI
    15
    MIT
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    Indexes local Markdown/text files into a SQLite database with vector embeddings and provides MCP tools for semantic search without cloud dependencies.
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    AGPL 3.0
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    An MCP server that provides AI assistants with access to Multi Theft Auto: San Andreas function documentation through vector similarity search and smart keyword expansion. It enables efficient information retrieval with features like deprecation warnings and SQLite caching for technical documentation.
    11
    47 npm
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    GPL 3.0
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    Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.
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    Enables LLMs to interact with Zvec vector database through tools for collection management, document operations, vector search, and AI-powered embeddings.
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    Apache 2.0
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    Enables AI assistants to interact with a Qdrant vector database by exposing collection, point, vector, payload, snapshot, search, recommendation, discovery, and observability operations as MCP tools.
    13
    34 PyPI
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    MIT
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    A long-horizon memory architecture for AI agents, providing a scalable, graph-based memory with causal typing and an MCP interface.
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    Business Source 1.1
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    An MCP server that implements memory with decay mechanics, allowing AI agents to store and retrieve memories that fade over time unless accessed, with a permanent journal for verification.
    3
    MIT
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    A 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.
    3
    62
    Apache 2.0
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    A persistent semantic memory system for Claude Code, using vector search and a judgment ledger to surface prior decisions and calibrate predictions.
    17
    MIT