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@@ -68,6 +81,13 @@ The Claude desktop application provides comprehensive support for MCP, enabling
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> ⓘ Note: The Claude.ai web application does not currently support MCP. MCP features are only available in the desktop application.
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### Claude Code
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Claude Code is an interactive agentic coding tool from Anthropic that helps you code faster through natural language commands. It supports MCP integration for prompts and tools, and also functions as an MCP server to integrate with other clients.
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**Key features:**
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- Tool and prompt support for MCP servers
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- Offers its own tools through an MCP server for integrating with other MCP clients
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### 5ire
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[5ire](https://github.com/nanbingxyz/5ire) is an open source cross-platform desktop AI assistant that supports tools through MCP servers.
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**Key features:**
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- Provides MCP tool support for Emacs.
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### fast-agent
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[fast-agent](https://github.com/evalstate/fast-agent) is a Python Agent framework, with simple declarative support for creating Agents and Workflows, with full multi-modal support for Anthropic and OpenAI models.
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**Key features:**
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- PDF and Image support, based on MCP Native types
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- Interactive front-end to develop and diagnose Agent applications, including passthrough and playback simulators
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- Built in support for "Building Effective Agents" workflows.
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- Deploy Agents as MCP Servers
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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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- Implements every pattern defined in [Building Effective Agents](https://www.anthropic.com/research/building-effective-agents).
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- Supports workflow pause/resume signals, such as waiting for human feedback.
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### oterm
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[oterm] is a terminal client for Ollama allowing users to create chats/agents.
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**Key features:**
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- Support for multiple fully customizable chat sessions with Ollama connected with tools.
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- Support for MCP tools.
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### Roo Code
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[Roo Code](https://roocode.com) enables AI coding assistance via MCP.
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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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### SpinAI
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[SpinAI](https://spinai.dev) is an open-source TypeScript framework for building observable AI agents. The framework provides native MCP compatibility, allowing agents to seamlessly integrate with MCP servers and tools.
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**Key features:**
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- Built-in MCP compatibility for AI agents
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- Open-source TypeScript framework
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- Observable agent architecture
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- Native support for MCP tools integration
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### Superinterface
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[Superinterface](https://superinterface.ai) is AI infrastructure and a developer platform to build in-app AI assistants with support for MCP, interactive components, client-side function calling and more.
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- Supports MCP tools in OpenSumi
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- Supports built-in IDE MCP servers and custom MCP servers
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### Daydreams
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[Daydreams](https://github.com/daydreamsai/daydreams) is a generative agent framework for executing anything onchain
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**Key features:**
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- Supports MCP Servers in config
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- Exposes MCP Client
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### Apify MCP Tester
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[Apify MCP Tester](https://github.com/apify/tester-mcp-client) is an open-source client that connects to any MCP server using Server-Sent Events (SSE).
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It is a standalone Apify Actor designed for testing MCP servers over SSE, with support for Authorization headers.
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It uses plain JavaScript (old-school style) and is hosted on Apify, allowing you to run it without any setup.
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**Key features:**
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- Connects to any MCP server via SSE.
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- Works with the [Apify MCP Server](https://apify.com/apify/actors-mcp-server) to interact with one or more Apify [Actors](https://apify.com/store).
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- Dynamically utilizes tools based on context and user queries (if supported by the server).
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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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## Remote MCP Support
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Our top priority is enabling[remote MCP connections](https://github.com/modelcontextprotocol/specification/discussions/102), allowing clients to securely connect to MCP servers over the internet. Key initiatives include:
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Our top priority is improving[remote MCP connections](https://github.com/modelcontextprotocol/specification/discussions/112), allowing clients to securely connect to MCP servers over the internet. Key initiatives include:
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description: 'Get started with the Model Context Protocol (MCP)'
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---
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<Note>Java SDK released! Check out [what else is new.](/development/updates)</Note>
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<Note>C# SDK released! Check out [what else is new.](/development/updates)</Note>
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MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.
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>
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Test and inspect your MCP servers with our interactive debugging tool
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- For bug reports and feature requests related to the MCP specification, SDKs, or documentation (open source), please [create a GitHub issue](https://github.com/modelcontextprotocol)
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- For discussions or Q&A about the MCP specification, use the [specification discussions](https://github.com/modelcontextprotocol/specification/discussions)
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- For discussions or Q&A about other MCP open source components, use the [organization discussions](https://github.com/orgs/modelcontextprotocol/discussions)
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- For bug reports, feature requests, and questions related to Claude.app and claude.ai's MCP integration, please email [email protected]
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- For bug reports, feature requests, and questions related to Claude.app and claude.ai's MCP integration, please email [email protected]
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