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  • F
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    一个基于Model Context Protocol的SQLite数据库查询服务,为AI应用提供标准化的数据库访问、安全的SQL查询执行以及表结构预览功能。
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  • F
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    D
    maintenance
    Enables semantic search and document management with support for text, PDF, and image uploads using your own Supabase database and OpenAI API keys. Supports multi-tenant deployment on Cloudflare Workers or local hosting.
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  • A
    license
    A
    quality
    A
    maintenance
    Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.
    12
    6
    MIT
  • A
    license
    A
    quality
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    maintenance
    Enables MCP clients to securely query databases, list tables, inspect table schemas, and test connections across Oracle, SQL Server, MySQL, PostgreSQL, and SQLite using read-only SQL tools.
    4
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.
    3
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    A Model Context Protocol server that exposes Firebase Firestore and Authentication to AI agents, supporting multi-project configurations and read operations.
    5
    33 npm
    MIT
  • A
    license
    B
    quality
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    maintenance
    Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.
    20
    6 npm
    20
    MIT
  • F
    license
    B
    quality
    C
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    Provides 17 standalone tools across calc, site, and catalog domains, enabling optics calculations, knowledge-base search, and read-only lens catalog queries via MCP without requiring an LLM or frontend.
    17
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  • A
    license
    C
    quality
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    maintenance
    Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.
    30
    20
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables LLM agents to accumulate and manage organizational knowledge across sessions in Neo4j, with enforced structural invariants and append-only semantics.
    2
    Apache 2.0
  • A
    license
    Not graded
    quality
    D
    maintenance
    A powerful AI service platform that provides complete MCP tool calling capabilities and RAG knowledge base functionality, enabling users to connect to multiple MCP servers and perform intelligent document search.
    Apache 2.0
  • A
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    Not graded
    quality
    B
    maintenance
    Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.
    MIT
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    quality
    B
    maintenance
    Provides a production-ready Model Context Protocol server with dual STDIO and Streamable HTTP transports, enabling file operations, memory, database queries, RAG, web search, GitHub integration, background tasks, and prompt-based workflows.
    MIT
  • A
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    quality
    D
    maintenance
    This MCP server provides AI-optimized access to Brazil's largest open data platform, Base dos Dados, enabling dataset search and direct BigQuery SQL execution for Brazilian public datasets.
    1
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI assistants to securely triage SuperOffice CRM support cases by retrieving tickets, running database diagnostics, searching knowledge bases, and orchestrating cross-system incident investigations.
    MIT