61 lines
No EOL
3 KiB
Text
61 lines
No EOL
3 KiB
Text
---
|
|
title: "Clients"
|
|
description: "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 | Notes |
|
|
|--------|-----------|---------|-------|----------|-------|
|
|
| Claude Desktop App | ✅ | ✅ | ✅ | ❌ | Full support for all MCP features except sampling |
|
|
| Zed | ❌ | ✅ | ✅ | ❌ | Prompts appear as slash commands |
|
|
| Sourcegraph Cody | ✅ | ❌ | ❌ | ❌ | Currently only 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](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.
|
|
|
|
**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](https://openctx.org/docs/providers/modelcontextprotocol) 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](https://github.com/modelcontextprotocol/python-sdk) or [TypeScript SDK Documentation](https://github.com/modelcontextprotocol/typescript-sdk)
|
|
|
|
## 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. |