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    Multi-modal RAG engine for AI assistants. Stores conversation history, conclusions, diffs, error traces, and other development artifacts in LanceDB with vector search, multi-factor scoring, and an LLM-driven consolidation pipeline.
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    MIT
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    Enables interaction with the Morphik multi-modal database system for document ingestion, retrieval, querying, and management. Supports text and file ingestion, semantic search with LLM-powered completions, and file system navigation with security controls.
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    ISC
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    A high-performance persistent memory layer for AI agents with multi-modal support, 47 retrieval channels, and 50-tier guardian chains, integrating 12+ memory approaches into a unified architecture.
    MIT
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    A pluggable and observable Retrieval-Augmented Generation framework that exposes hybrid search and document management tools via the Model Context Protocol. It features a complete ingestion pipeline with multi-modal support, automated evaluation using Ragas, and a Streamlit dashboard for real-time tracking.
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    MIT
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    Local-first MCP server enabling cross-modal search across text, images, documents, video, and audio transcripts. Provides 26 tools for ingesting, searching, and navigating local file systems with a 3-stage pipeline including reranking.
    3
    MIT
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    Provides two-modal code search (lexical via Zoekt and semantic via ChromaDB embeddings) for AI coding agents through MCP tools, enabling fast regex and meaning-based code lookup.
    MIT
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    A Multi-modal Conversation Protocol (MCP) server that enables interacting with web APIs through a curl-like interface, providing access to various websites and APIs with user authentication and response transformations.
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    ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.
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    1,074
    Apache 2.0
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    An MCP server that retrieves and provides AI model information from OpenAI, Anthropic, and Google through a unified interface.
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    MIT
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    IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real
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    JavaScript
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    A Model Context Protocol server that enables LLMs to interact directly with MongoDB databases, allowing users to query collections, inspect schemas, and manage data through natural language.
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    Connects Claude to a personal knowledge base with hybrid search over code, documents, and images. Allows the AI assistant to retrieve and answer from your own files during conversations.
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    MIT