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docs/clients.mdx

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@@ -58,7 +58,7 @@ This page provides an overview of applications that support the Model Context Pr
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| [TheiaAI/TheiaIDE][TheiaAI/TheiaIDE] ||||||| Supports tools for Agents in Theia AI and the AI-powered Theia IDE |
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| [Tome][Tome] ||||||| Supports tools, manages MCP servers. |
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| [TypingMind App][TypingMind App] ||||||| Supports tools at app-level (appear as plugins) or when assigned to Agents |
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| [VS Code GitHub Copilot][VS Code] | | ||| || Supports dynamic tool/roots discovery, secure secret configuration, and explicit tool prompting |
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| [VS Code GitHub Copilot][VS Code] | | ||| || Supports dynamic tool/roots discovery, secure secret configuration, and explicit tool prompting |
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| [Warp][Warp] ||||||| Supports tools, resources, and most of the discovery criteria |
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| [WhatsMCP][WhatsMCP] ||||||| Supports tools for Remote MCP Servers in WhatsApp |
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| [Windsurf Editor][Windsurf] ||||||| Supports tools with AI Flow for collaborative development. |
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- Full support of all major MCP features (tools, prompts, resources, and subscriptions)
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- Fast, seamless UI for debugging MCP capabilities
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- MCP config integration (Claude, VSCode, etc.) for fast first-time experience in testing MCPs
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- Integration with history, varibles, and collections for re-use and collaboration
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- Integration with history, variables, and collections for reuse and collaboration
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### Slack MCP Client
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### Witsy
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[Witsy](https://github.com/nbonamy/witsy) is an AI desktop assistant, supoorting Anthropic models and MCP servers as LLM tools.
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[Witsy](https://github.com/nbonamy/witsy) is an AI desktop assistant, supporting Anthropic models and MCP servers as LLM tools.
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**Key features:**
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docs/quickstart/client.mdx

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description: "Get started building your own client that can integrate with all MCP servers."
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---
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In this tutorial, you'll learn how to build a LLM-powered chatbot client that connects to MCP servers. It helps to have gone through the [Server quickstart](/quickstart/server) that guides you through the basic of building your first server.
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In this tutorial, you'll learn how to build an LLM-powered chatbot client that connects to MCP servers. It helps to have gone through the [Server quickstart](/quickstart/server) that guides you through the basics of building your first server.
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<Tabs>
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<Tab title="Python">
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command,
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args: [serverScriptPath],
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});
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this.mcp.connect(this.transport);
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await this.mcp.connect(this.transport);
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const toolsResult = await this.mcp.listTools();
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this.tools = toolsResult.tools.map((tool) => {
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});
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const finalText = [];
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const toolResults = [];
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for (const content of response.content) {
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if (content.type === "text") {
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name: toolName,
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arguments: toolArgs,
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});
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toolResults.push(result);
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finalText.push(
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`[Calling tool ${toolName} with args ${JSON.stringify(toolArgs)}]`
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);
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dotnet add package ModelContextProtocol --prerelease
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dotnet add package Anthropic.SDK
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dotnet add package Microsoft.Extensions.Hosting
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dotnet add package Microsoft.Extensions.AI
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```
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## Setting up your API key

docs/quickstart/server.mdx

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```
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and set the `spring.ai.mcp.client.stdio.servers-configuration` property to point to your `claude_desktop_config.json`.
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You can re-use the existing Anthropic Desktop configuration:
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You can reuse the existing Anthropic Desktop configuration:
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```properties
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spring.ai.mcp.client.stdio.servers-configuration=file:PATH/TO/claude_desktop_config.json
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<Note>
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When creating the `ApplicationHostBuilder`, ensure you use `CreateEmptyApplicationBuilder` instead of `CreateDefaultBuilder`. This ensures that the server does not write any additional messages to the console. This is only neccessary for servers using STDIO transport.
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When creating the `ApplicationHostBuilder`, ensure you use `CreateEmptyApplicationBuilder` instead of `CreateDefaultBuilder`. This ensures that the server does not write any additional messages to the console. This is only necessary for servers using STDIO transport.
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</Note>
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docs/sdk/java/mcp-server.mdx

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</Tabs>
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The `McpSchema.CompletionReference` definition defines the type (`PromptRefernce` or `ResourceRefernce`) and the identifier for the completion specification (e.g handler).
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The handler function processes requests and returns the complition response.
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The handler function processes requests and returns the completion response.
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The first argument is `McpAsyncServerExchange` for client interaction, and the second argument is a `CompleteRequest` instance.
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Check the [using completion](/sdk/java/mcp-client#using-completion) to learn how to use the completion capabilities on the client side.

docs/specification/draft/basic/authorization.mdx

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Authorization servers **MUST** validate exact redirect URIs against pre-registered values to prevent redirection attacks.
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MCP clients **SHOULD** use and verify state parameters in the authorization code flow
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and discard any results that do not include or have a mis-match with the original state.
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and discard any results that do not include or have a mismatch with the original state.
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Authorization servers **MUST** take precautions to prevent redirecting user agents to untrusted URI's, following suggestions laid out in [OAuth 2.1 Section 7.12.2](https://datatracker.ietf.org/doc/html/draft-ietf-oauth-v2-1-12#section-7.12.2)
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