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    Enables AI assistants to query and analyze databases using natural language through MCP and HTTP API, supporting 17+ databases and integration with 50+ platforms.
    138
    MIT
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    A read-only PostgreSQL MCP server for AI coding agents that exposes database schema and sample data as tools, with LLM-powered semantic search enriched by a user-authored semantic layer.
    4
    MIT
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    A server that enables LLMs like Claude to interact with Azure Cosmos DB databases through natural language queries, acting as a translator between AI assistants and database systems.
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    3
    MIT
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    An MCP server that bridges AI assistants with data warehouses through Cube.js to enable governed, natural language semantic analytics queries. It provides tools for metadata discovery and secure query execution while enforcing governance policies like PII blocking and access limits.
    3
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    1
    MIT
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    DEVONthink 4 connector with six tools for search, retrieval, and write operations. Dry-run by default, append-only audit log, selective undo via audit_id; macOS-only, MIT, local-only, clean-room implementation.
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    MIT
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    Provides programmatic access to UK legal documents with hybrid semantic search and Model Context Protocol integration for AI assistants.
    62
    MIT
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    Provides read-only access to databases for MCP-compatible AI tools, allowing schema exploration and SELECT queries without exposing credentials or risking data changes.
    62
    3
    MIT
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    Provides a local, persistent context database for AI tools via MCP, enabling them to recall user preferences, decisions, and experiences across sessions. It is fully local with optional sync, and works with any MCP client.
    581
    Business Source 1.1
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    A temporal knowledge graph system that enables users to record and query architectural decisions, implementation patterns, and project failures. It integrates with Claude to provide hybrid search, timeline tracking, and automated knowledge gap detection using graph analysis.
    3
    MIT
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    This MCP server provides evidence-based advice on vector database backends by retrieving measured benchmarks and operational traps, enabling you to ask questions and compare backends through natural language.
    MIT
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    Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.
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    335
    MIT