Merge branch 'main' of github.com:modelcontextprotocol/docs into zack-lee/thumbs-up-feedback-and-contributing
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Zachary Lee
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11
clients.mdx
11
clients.mdx
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@ -12,10 +12,12 @@ This page provides an overview of applications that support the Model Context Pr
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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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[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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[Resources]: https://modelcontextprotocol.io/docs/concepts/resources
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[Prompts]: https://modelcontextprotocol.io/docs/concepts/prompts
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@ -53,6 +55,15 @@ The Claude desktop application provides comprehensive support for MCP, enabling
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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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## 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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@ -7,8 +7,12 @@ Resources are a core primitive in the Model Context Protocol (MCP) that allow se
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<Note>
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Resources are designed to be **application-controlled**, meaning that the client application can decide how and when they should be used.
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Different MCP clients may handle resources differently. For example:
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- Claude Desktop currently requires users to explicitly select resources before they can be used
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- Other clients might automatically select resources based on heuristics
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- Some implementations may even allow the AI model itself to determine which resources to use
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For example, one application may require users to explicitly select resources, while another could automatically select them based on heuristics or even at the discretion of the AI model itself.
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Server authors should be prepared to handle any of these interaction patterns when implementing resource support. In order to expose data to models automatically, server authors should use a **model-controlled** primitive such as [Tools](./tools).
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</Note>
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## Overview
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@ -477,7 +477,7 @@ Let's build your first MCP server in Python! We'll create a weather server that
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## Available transports
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While this guide uses stdio transport, MCP supports additonal transport options:
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While this guide uses stdio transport, MCP supports additional transport options:
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### SSE (Server-Sent Events)
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@ -638,18 +638,15 @@ uvicorn.run(app, host="0.0.0.0", port=8000)
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<Step title="Add resource templates">
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```python
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@self.list_resources()
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async def list_resources(self) -> ListResourcesResult:
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return ListResourcesResult(
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resources=[...],
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resourceTemplates=[
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ResourceTemplate(
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uriTemplate="weather://{city}/current",
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name="Current weather for any city",
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mimeType="application/json"
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)
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]
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)
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@app.list_resource_templates()
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async def list_resource_templates() -> list[ResourceTemplate]:
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return [
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ResourceTemplate(
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uriTemplate="weather://{city}/current",
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name="Current weather for any city",
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mimeType="application/json"
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)
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]
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```
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</Step>
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</Steps>
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@ -751,7 +748,7 @@ uvicorn.run(app, host="0.0.0.0", port=8000)
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pass
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def json(self):
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return nock_forecast_response
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return mock_forecast_response
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class AsyncClient():
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def __aenter__(self):
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@ -41,6 +41,10 @@ This guide uses the OpenWeatherMap API. You'll need a free API key from [OpenWea
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```bash
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OPENWEATHER_API_KEY=your-api-key-here
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```
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Make sure to add your environment file to `.gitignore`
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```bash
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.env
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```
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</Step>
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</Steps>
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@ -342,18 +346,18 @@ This guide uses the OpenWeatherMap API. You'll need a free API key from [OpenWea
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}
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return {
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content: {
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mimeType: "application/json",
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content: [{
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type: "text",
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text: JSON.stringify(forecasts, null, 2)
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}
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}]
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};
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} catch (error) {
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if (axios.isAxiosError(error)) {
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return {
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content: {
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mimeType: "text/plain",
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content: [{
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type: "text",
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text: `Weather API error: ${error.response?.data.message ?? error.message}`
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},
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}],
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isError: true,
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}
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}
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@ -368,7 +372,6 @@ This guide uses the OpenWeatherMap API. You'll need a free API key from [OpenWea
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<Step title="Build and test">
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```bash
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npm run build
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npm link
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```
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</Step>
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</Steps>
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@ -383,7 +386,8 @@ This guide uses the OpenWeatherMap API. You'll need a free API key from [OpenWea
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{
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"mcpServers": {
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"weather": {
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"command": "weather-server",
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"command": "node",
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"args": ["/path/to/weather-server/build/index.js"],
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"env": {
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"OPENWEATHER_API_KEY": "your-api-key",
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}
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@ -561,7 +565,7 @@ npm run build
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Look for detailed error messages in the Claude Desktop logs:
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```bash
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# Monitor logs
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tail -n 20 -f ~/Library/Application\ Support/Claude/mcp*.log
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tail -n 20 -f ~/Library/Logs/Claude/mcp*.log
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```
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### Type errors
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