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107,757 servers. Updated
20 Best GitHub MCP Servers: compared and ranked, October 2026Ranked from 1,950 matching servers on stars, growth, downloads and maintenance. Updated .

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    license
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    An MCP server that caches your GitHub starred repositories in a local SQLite database and lets you search, list, and retrieve details about them through any MCP client (Claude Desktop, Cursor, VS Code, etc.), with automatic freshness checks via GitHub's ETag mechanism.
    5
    1
    MIT
  • A
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    Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.
    2
    AGPL 3.0
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    Turns any OData V2 or V4 service, SAP Gateway included, into MCP tools that AI clients such as Claude, ChatGPT, Copilot, and Cursor can call without code by reading $metadata. It lets models discover entity sets and fields, then query services through built-in read-only tools.
    AGPL 3.0
  • A
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    D
    maintenance
    Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.
    1
    GPL 3.0
  • A
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    quality
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    A Model Context Protocol server that provides tools for searching private GitHub repositories, enabling access to repository files, commit history, and issues with automatic handling of rate limiting and error handling.
    4
    17 npm
    9
    MIT
  • A
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    This read-only MCP Server allows you to connect to GitHub data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).
    MIT
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    Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.
    42 npm
    MIT
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    A
    maintenance
    Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.
    MIT
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    A
    maintenance
    Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.
    MIT
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    A
    maintenance
    Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.
    MIT
  • A
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    A
    maintenance
    Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.
    MIT
  • A
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    quality
    A
    maintenance
    Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.
    MIT
  • A
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    maintenance
    MCP server that translates natural-language questions into SQL, validates every query structurally, and executes approved read-only queries against a SQLite database, returning results and rejections.
    MIT
  • A
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    quality
    A
    maintenance
    Enables LLMs and MCP clients to discover and use generated CRUD services through MCP tools and resources, exposing actions like create, update, delete, and read-only list/get access alongside REST endpoints.
    MIT
  • A
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    maintenance
    Enables Claude to translate natural-language business questions into safe, read-only SQL queries by exposing tools for listing tables, inspecting schemas, and executing row-capped SELECT statements against PostgreSQL.
    MIT
  • A
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    quality
    A
    maintenance
    Enables LLMs and AI assistants to discover and use tools and resources for CRUD operations on generated services, providing direct interaction with the same data exposed by REST endpoints.
    MIT