Clients
A list of applications that support MCP integrations
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.
Feature support matrix
| Client | Resources | Prompts | Tools | Sampling | Roots | Notes |
|---|---|---|---|---|---|---|
| Claude Desktop App | ✅ | ✅ | ✅ | ❌ | ❌ | Full support for all MCP features |
| Zed | ❌ | ✅ | ❌ | ❌ | ❌ | Prompts appear as slash commands |
| Sourcegraph Cody | ✅ | ❌ | ❌ | ❌ | ❌ | Supports resources through OpenCTX |
Client details
Claude Desktop App
The Claude desktop application provides comprehensive support for MCP, enabling deep integration with local tools and data sources.
Key features:
- Full support for resources, allowing attachment of local files and data
- Support for prompt templates
- Tool integration for executing commands and scripts
- Local server connections for enhanced privacy and security
ⓘ Note: The Claude.ai web application does not currently support MCP. MCP features are only available in the desktop application.
Zed
Zed is a high-performance code editor with built-in MCP support, focusing on prompt templates and tool integration.
Key features:
- Prompt templates surface as slash commands in the editor
- Tool integration for enhanced coding workflows
- Tight integration with editor features and workspace context
- Does not support MCP resources
Sourcegraph Cody
Cody is Sourcegraph’s AI coding assistant, which implements MCP through OpenCTX.
Key features:
- Support for MCP resources
- Integration with Sourcegraph’s code intelligence
- Uses OpenCTX as an abstraction layer
- Future support planned for additional MCP features
Adding MCP support to your application
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.
Benefits of adding MCP support:
- Enable users to bring their own context and tools
- Join a growing ecosystem of interoperable AI applications
- Provide users with flexible integration options
- Support local-first AI workflows
To get started with implementing MCP in your application, check out our Python or TypeScript SDK Documentation
Updates and corrections
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.