102 lines
5.5 KiB
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102 lines
5.5 KiB
Text
---
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title: "Clients"
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description: "A list of applications that support MCP integrations"
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---
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This page provides an overview of applications that support the Model Context Protocol (MCP). Each client may support different MCP features, allowing for varying levels of integration with MCP servers.
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## Feature support matrix
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| Client | [Resources] | [Prompts] | [Tools] | [Sampling] | Roots | Notes |
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|---------------------------|-------------|-----------|---------|------------|-------|---------------------------------------------------|
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| [Claude Desktop App][Claude] | ✅ | ✅ | ✅ | ❌ | ❌ | Full support for all MCP features |
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| [Zed][Zed] | ❌ | ✅ | ❌ | ❌ | ❌ | Prompts appear as slash commands |
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| [Sourcegraph Cody][Cody] | ✅ | ❌ | ❌ | ❌ | ❌ | Supports resources through OpenCTX |
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| [Firebase Genkit][Genkit] | ⚠️ | ✅ | ✅ | ❌ | ❌ | Supports resource list and lookup through tools. |
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| [Continue][Continue] | ✅ | ✅ | ✅ | ❌ | ❌ | Full support for all MCP features |
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| [GenAIScript][GenAIScript] | ❌ | ❌ | ✅ | ❌ | ❌ | Supports tools. |
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[Claude]: https://claude.ai/download
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[Zed]: https://zed.dev
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[Cody]: https://sourcegraph.com/cody
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[Genkit]: https://github.com/firebase/genkit
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[Continue]: https://github.com/continuedev/continue
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[GenAIScript]: https://microsoft.github.io/genaiscript/reference/scripts/mcp-tools/
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[Resources]: https://modelcontextprotocol.io/docs/concepts/resources
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[Prompts]: https://modelcontextprotocol.io/docs/concepts/prompts
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[Tools]: https://modelcontextprotocol.io/docs/concepts/tools
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[Sampling]: https://modelcontextprotocol.io/docs/concepts/sampling
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## Client details
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### Claude Desktop App
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The Claude desktop application provides comprehensive support for MCP, enabling deep integration with local tools and data sources.
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**Key features:**
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- Full support for resources, allowing attachment of local files and data
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- Support for prompt templates
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- Tool integration for executing commands and scripts
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- Local server connections for enhanced privacy and security
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> ⓘ Note: The Claude.ai web application does not currently support MCP. MCP features are only available in the desktop application.
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### Zed
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[Zed](https://zed.dev/docs/assistant/model-context-protocol) is a high-performance code editor with built-in MCP support, focusing on prompt templates and tool integration.
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**Key features:**
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- Prompt templates surface as slash commands in the editor
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- Tool integration for enhanced coding workflows
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- Tight integration with editor features and workspace context
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- Does not support MCP resources
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### Sourcegraph Cody
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[Cody](https://openctx.org/docs/providers/modelcontextprotocol) is Sourcegraph's AI coding assistant, which implements MCP through OpenCTX.
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**Key features:**
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- Support for MCP resources
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- Integration with Sourcegraph's code intelligence
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- Uses OpenCTX as an abstraction layer
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- Future support planned for additional MCP features
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### Firebase Genkit
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[Genkit](https://github.com/firebase/genkit) is Firebase's SDK for building and integrating GenAI features into applications. The [genkitx-mcp](https://github.com/firebase/genkit/tree/main/js/plugins/mcp) plugin enables consuming MCP servers as a client or creating MCP servers from Genkit tools and prompts.
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**Key features:**
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- Client support for tools and prompts (resources partially supported)
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- Rich discovery with support in Genkit's Dev UI playground
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- Seamless interoperability with Genkit's existing tools and prompts
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- Works across a wide variety of GenAI models from top providers
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### Continue
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[Continue](https://github.com/continuedev/continue) is an open-source AI code assistant, with built-in support for all MCP features.
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**Key features**
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- Type "@" to mention MCP resources
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- Prompt templates surface as slash commands
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- Use both built-in and MCP tools directly in chat
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- Supports VS Code and JetBrains IDEs, with any LLM
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### GenAIScript
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Programmatically assemble prompts for LLMs using [GenAIScript](https://microsoft.github.io/genaiscript/) (in JavaScript). Orchestrate LLMs, tools, and data in JavaScript.
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**Key features:**
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- JavaScript toolbox to work with prompts
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- Abstraction to make it easy and productive
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- Seamless Visual Studio Code integration
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## Adding MCP support to your application
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If you've added MCP support to your application, we encourage you to submit a pull request to add it to this list. MCP integration can provide your users with powerful contextual AI capabilities and make your application part of the growing MCP ecosystem.
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Benefits of adding MCP support:
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- Enable users to bring their own context and tools
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- Join a growing ecosystem of interoperable AI applications
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- Provide users with flexible integration options
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- Support local-first AI workflows
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To get started with implementing MCP in your application, check out our [Python](https://github.com/modelcontextprotocol/python-sdk) or [TypeScript SDK Documentation](https://github.com/modelcontextprotocol/typescript-sdk)
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## Updates and corrections
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This list is maintained by the community. If you notice any inaccuracies or would like to update information about MCP support in your application, please submit a pull request or [open an issue in our documentation repository](https://github.com/modelcontextprotocol/docs/issues).
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