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20 Best GitHub MCP Servers: compared and ranked, November 2026Ranked from 2,153 matching servers on stars, growth, downloads and maintenance. Updated .

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  • A
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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
    23 npm
    10
    MIT
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    Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.
    MIT
  • F
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    Read-only MCP server that proxies The Game Pensieve API over Streamable HTTP, letting AI assistants query a personal game collection via tools like search, filters, and summaries. Supports OAuth 2.1 enforcement and owner-scoped access.
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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
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    Enables AI agents and MCP clients to browse and search GitHub repositories, manage issues and pull requests, and query or update a local SQLite database through validated tools. It also supports guided Claude Code skills for repository exploration, database assistance, and health checks.
    12
    MIT
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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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    Enables AI agents to search and retrieve UK company data, including company details by Companies House number, group ownership structures, website associations, and Real-Time Industrial Classification definitions.
    MIT
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    Enables AI agents to discover and query data federated across MySQL/MariaDB, PostgreSQL, ClickHouse, S3 and Kafka with SQL, exposing tools to list databases, schemas, tables and connections, describe columns, search objects, inspect table statistics, run EXPLAIN, and execute arbitrary statements. It runs locally over stdio against a PostgreSQL-wire endpoint and returns structured results or SQLSTATE-coded errors.
    8
    Apache 2.0
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    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
    16 npm
    288
    MIT
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    Enables local-first expense logging, editing, and analysis through natural language conversation, backed by a SQLite database and accessible via MCP over stdio.
    8
    MIT
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    Enables MCP clients to interact with Odoo models through generic read and write tools, with read-only mode by default and Odoo ACLs as the authority.
    5
    34 npm
    MIT
  • F
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    Provides read-only EspoCRM access for AI assistants, enabling record retrieval and preparation of signed change sets without direct modification or deletion.
    7
    -
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    MCP server that reads local SQLite database populated by a Playwright scraper to provide daily summary, food log, weight history, and water log from LoseIt.
    MIT
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    Enables an AI agent to run read-only SQL over local CSV, Parquet, and JSON files through MCP tools, with directory sandboxing, statement gating, timeouts, and query timeouts that keep access confined to permitted folders. Results are shaped for small context windows with row caps, truncation notices, and markdown/CSV/JSON output.
    MIT
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    Lets Claude Desktop, Claude Code, and other MCP clients map the structure of a SQLite database and run read-only SQL queries against it, returning compact Markdown results. Multi-layered protections make any write impossible, so a database can be explored without reviewing each query first.
    MIT
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    Enables AI assistants to query and analyze databases using natural language through MCP and HTTP API. Supports 17+ databases and integrates with 55+ platforms.
    130 npm
    MIT
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    Enables AI agents to inspect schemas, walk Delta table history, run read-only DuckDB queries, and check data-quality and job-run status safely.
    MIT
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    Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.
    Apache 2.0
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    A production-grade Model Context Protocol server that enables secure management of context data through a React dashboard, supporting ZIP processing, context approval workflows, and system monitoring.
    529 npm
    -
  • F
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    HTTP MCP server that reads from and writes to a PostgreSQL database (bankdb). Provides tools for querying and managing customer, account, and transaction data.
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  • -
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    Enables LLMs to interact with OpenEHR electronic health record systems by retrieving clinical archetypes, generating AQL queries from natural language, and executing queries against on-premise EHR databases. Supports OpenEHR Clinical Knowledge Manager integration and custom IIS-hosted EHR APIs for comprehensive medical data access.
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  • F
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    An MCP server that enables AI assistants to query and interact with SQLite databases through natural language. It includes built-in security guardrails such as PII redaction, SQL injection blocking, and query rate limiting.
    -
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    SchemaBrain is an MCP server that sits between AI agents (Claude, Cursor, Windsurf) and your SQL database as a read-only trust + intelligence layer. The agent never writes SQL — 12 tools compile it from definitions you control, PII and secret categories are refused before the query runs, and every call lands in a tamper-evident (SHA-256-chained) audit log. Postgres today.
    12
    19 PyPI
    12
    Apache 2.0
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    Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.
    12
    6
    663 PyPI
    973
    Apache 2.0