This page showcases applications that support the Model Context Protocol (MCP). Each client may support different MCP features:
| Feature | Description |
|---|---|
| Server-exposed data and content | |
| Pre-defined templates for LLM interactions | |
| Executable functions that LLMs can invoke | |
| Support for tools/prompts/resources changed notifications | |
| Server-provided guidance for LLMs | |
| Server-initiated LLM completions | |
| Filesystem boundary definitions | |
| User information requests | |
| Client ID Metadata Document support | |
| Dynamic Client Registration support | |
| Long-running operation tracking | |
| Interactive HTML interfaces |
This list is maintained by the community. If you notice any inaccuracies or would like to add or update information about MCP support in your application, please submit a pull request.
Client details
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