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README.md
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README.md
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> A list of Model Context Protocol (MCP) servers curated by [ChatHub](https://chathub.gg/?utm_source=mcp)
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## Sponsors
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<p align="center">
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<a href="https://get.brightdata.com/ohiwqscr4mne">
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<img src="https://mintlify.s3.us-west-1.amazonaws.com/brightdata/logo/light.svg" width="200" alt="Bright Data Logo">
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</a>
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</p>
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## Reference Servers
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These servers aim to demonstrate MCP features and the TypeScript and Python SDKs.
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- **[Browserbase](https://github.com/browserbase/mcp-server-browserbase)** - Automate browser interactions in the cloud (e.g. web navigation, data extraction, form filling, and more)
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- **[BrowserStack](https://github.com/browserstack/mcp-server)** – Bring the full power of BrowserStack’s [Test Platform](https://www.browserstack.com/test-platform) to your AI tools, making testing faster and easier for every developer and tester on your team.
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- **[Bucket](https://github.com/bucketco/bucket-javascript-sdk/tree/main/packages/cli#model-context-protocol)** - Flag features, manage company data, and control feature access using [Bucket](https://bucket.co)
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- **[Buildkite](https://github.com/buildkite/buildkite-mcp-server)** - Manage [Buildkite](https://buildkite.com) pipelines and builds.
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- **[Buildkite](https://github.com/buildkite/buildkite-mcp-server)** - Manage [Buildkite](https://buildkite.com) pipelines and builds.
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- **[Campertunity](https://github.com/campertunity/mcp-server)** - Search campgrounds around the world on campertunity, check availability, and provide booking links.
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- **[Chargebee](https://github.com/chargebee/agentkit/tree/main/modelcontextprotocol)** - MCP Server that connects AI agents to [Chargebee platform](https://www.chargebee.com).
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- **[Chart](https://github.com/antvis/mcp-server-chart)** - 🤖 A Model Context Protocol server for generating visual charts using [AntV](https://github.com/antvis).
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- **[Dart](https://github.com/its-dart/dart-mcp-server)** - Interact with task, doc, and project data in [Dart](https://itsdart.com), an AI-native project management tool
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- **[DataWorks](https://github.com/aliyun/alibabacloud-dataworks-mcp-server)** - A Model Context Protocol (MCP) server that provides tools for AI, allowing it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Aliyun Open API and enables AI agents to perform cloud resources operations seamlessly.
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- **[DealX](https://github.com/DealExpress/mcp-server)** - MCP Server for DealX platform
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- **[Debugg AI](https://github.com/debugg-ai/debugg-ai-mcp)** - Enable your code gen agents to create & run 0-config end-to-end tests against new code changes in remote browsers via the [Debugg AI](https://debugg.ai) testing platform.
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- **[Debugg AI](https://github.com/debugg-ai/debugg-ai-mcp)** - Enable your code gen agents to create & run 0-config end-to-end tests against new code changes in remote browsers via the [Debugg AI](https://debugg.ai) testing platform.
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- **[dbt](https://github.com/dbt-labs/dbt-mcp)** - Official MCP server for [dbt (data build tool)](https://www.getdbt.com/product/what-is-dbt) providing integration with dbt Core/Cloud CLI, project metadata discovery, model information, and semantic layer querying capabilities.
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- **[DevHub](https://github.com/devhub/devhub-cms-mcp)** - Manage and utilize website content within the [DevHub](https://www.devhub.com) CMS platform
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- **[DeepResearch](https://github.com/OctagonAI/octagon-deep-research-mcp)** - Lightning-Fast, High-Accuracy Deep Research Agent 👉 8–10x faster 👉 Greater depth & accuracy 👉 Unlimited parallel runs
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- **[Jetty.io](https://github.com/jettyio/mlcbakery/tree/main/mcp_server)** — Work on dataset metadata with MLCommons Croissant validation and creation.
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- **[Kagi Search](https://github.com/kagisearch/kagimcp)** - Search the web using Kagi's search API
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- **[Keboola](https://github.com/keboola/keboola-mcp-server)** - Build robust data workflows, integrations, and analytics on a single intuitive platform.
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- **[Knit MCP](https://developers.getknit.dev/docs/knit-mcp-server-getting-started )** - Connect with 10,000+ tools across HRIS, ATS, CRM, Accounting, Calendar, Meeting, Ticketing, and more categories.
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- **[Knit MCP](https://developers.getknit.dev/docs/knit-mcp-server-getting-started)** - Connect with 10,000+ tools across HRIS, ATS, CRM, Accounting, Calendar, Meeting, Ticketing, and more categories.
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- **[Last9](https://github.com/last9/last9-mcp-server)** - Seamlessly bring real-time production context—logs, metrics, and traces—into your local environment to auto-fix code faster.
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- **[Logfire](https://github.com/pydantic/logfire-mcp)** - Provides access to OpenTelemetry traces and metrics through Logfire.
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- **[Langfuse Prompt Management](https://github.com/langfuse/mcp-server-langfuse)** - Open-source tool for collaborative editing, versioning, evaluating, and releasing prompts.
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- **[Zapier](https://zapier.com/mcp)** - Connect your AI Agents to 8,000 apps instantly.
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- **[ZenML](https://github.com/zenml-io/mcp-zenml)** - Interact with your MLOps and LLMOps pipelines through your [ZenML](https://www.zenml.io) MCP server
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## Community Servers
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A growing set of community-developed and maintained servers demonstrates various applications of MCP across different domains.
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- **[MCP Open Library](https://github.com/8enSmith/mcp-open-library)** - A Model Context Protocol (MCP) server for the Open Library API that enables AI assistants to search for book and author information.
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- **[MCP-SearXNG-Enhanced Web Search](https://github.com/OvertliDS/mcp-searxng-enhanced)** - An enhanced MCP server for SearXNG web searching, utilizing a category-aware web-search, web-scraping, and includes a date/time retrieval tool.
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- **[Mermaid](https://github.com/hustcc/mcp-mermaid)** - Generate [mermaid](https://mermaid.js.org/) diagram and chart with AI MCP dynamically.
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- **[Memory-Plus](https://github.com/Yuchen20/Memory-Plus)** a lightweight, local RAG memory store to record, retrieve, update, delete, and visualize persistent "memories" across sessions—perfect for developers working with multiple AI coders (like Windsurf, Cursor, or Copilot) or anyone who wants their AI to actually remember them.
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- **[Memory-Plus](https://github.com/Yuchen20/Memory-Plus)** a lightweight, local RAG memory store to record, retrieve, update, delete, and visualize persistent "memories" across sessions—perfect for developers working with multiple AI coders (like Windsurf, Cursor, or Copilot) or anyone who wants their AI to actually remember them.
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- **[Minima](https://github.com/dmayboroda/minima)** - Local RAG (on-premises) with MCP server.
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- **[Mongo](https://github.com/QuantGeekDev/mongo-mcp)** - A Model Context Protocol (MCP) server that enables LLMs to interact directly with MongoDB databases
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- **[MongoDB](https://github.com/kiliczsh/mcp-mongo-server)** - A Model Context Protocol Server for MongoDB
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- **[YouTube](https://github.com/anaisbetts/mcp-youtube)** - Fetch YouTube subtitles
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## Clients
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- **[mcp-cli](https://github.com/wong2/mcp-cli)** a cli inspector for MCP servers
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- **[mcp-client](https://github.com/rakesh-eltropy/mcp-client)** MCP REST API and CLI client for interacting with MCP servers, supports OpenAI, Claude, Gemini, Ollama etc.
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- **[MCP-Bridge](https://github.com/SecretiveShell/MCP-Bridge)** 🐍 an openAI middleware proxy to use mcp in any existing openAI compatible client
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