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    Model Context Protocol (MCP) server for TigerGraph that lets AI agents interact with TigerGraph through the MCP standard using pyTigerGraph's async APIs.
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    3
    Apache 2.0
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    Enables interaction with KDB.AI through natural language for vector database operations, similarity searches, hybrid search, and advanced data analysis.
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    Apache 2.0
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    Provides intelligent, persistent memory for AI assistants with semantic search, natural language queries, and OAuth-based team collaboration, enabling context-aware conversations across multiple clients.
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    Apache 2.0
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    MCP server for compressing AI embeddings by 5-7x using TurboQuant (PolarQuant + QJL), with tools to compress, decompress, estimate savings, and embed+compress vectors.
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    MIT
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    Persistent AI memory server with 3-layer hybrid search (vector + FTS5 + keyword), confidence scoring via Reciprocal Rank Fusion, episodic/profile memory, and 16 tools. Zero LLM dependency. Works standalone with Claude Desktop and Claude Code. MIT licensed.
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    Business Source 1.1
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    A high-performance FastAPI server supporting Model Context Protocol (MCP) for seamless integration with Large Language Models, featuring REST, GraphQL, and WebSocket APIs, along with real-time monitoring and vector search capabilities.
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    MIT
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    RAGX MCP Server enables retrieval-augmented generation with document ingestion, hybrid search, and agentic answering using Claude, exposing tools for querying, searching, and managing documents.
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    2
    MIT
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    Wraps n8n with an MCP server and vector storage to enable semantic search, management, and execution of automated workflows. It integrates with other tools to make workflows searchable and orchestratable within a larger automation ecosystem.
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    MIT
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    Enables interaction with DataStax Astra DB through the Model Context Protocol. Provides database connectivity and operations for Astra DB instances via secure token-based authentication.
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    MIT
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    Enables AI assistants to interact with MariaDB databases through standard SQL operations and advanced vector/embedding-based search. Supports database management, schema inspection, and semantic document storage and retrieval with multiple embedding providers.
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    MIT
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    A Model Context Protocol server integration that creates a persistent, searchable working memory for AI-assisted development by enabling automated context recall and knowledge persistence in Chroma, the open-source embedding database.
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    26
    MIT
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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.
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    MIT
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    An MCP server that enables AI assistants to directly interact with Elasticsearch for searching, aggregating, and retrieving documents from indices, supporting full-text search, semantic search, and various query modes.
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    7
    MIT