ACP to MCP Adapter
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ACP to MCP Adapteruse "echo" agent with the "Hello world" input"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Connect ACP Agents to MCP Applications Seamlessly
The ACP to MCP Adapter is a lightweight standalone server that acts as a bridge between two AI ecosystems: Agent Communication Protocol (ACP) for agent-to-agent communication and Model Context Protocol (MCP) for connecting AI models to external tools. It allows MCP applications (like Claude Desktop) to discover and interact with ACP agents as resources.
Capabilities & Tradeoffs
This adapter enables interoperability between ACP and MCP with specific benefits and tradeoffs:
Benefits
Makes ACP agents discoverable as MCP resources
Exposes ACP agent runs as MCP tools
Bridges two ecosystems with minimal configuration
Current Limitations
ACP agents become MCP tools instead of conversational peers
No streaming of incremental updates
No shared memory across servers
Basic content translation between formats without support for complex data structures
This adapter is best for situations where you need ACP agents in MCP environments and accept these compromises.
Related MCP server: A2A MCP Server
Requirements
Python 3.11 or higher
Installed Python packages:
acp-sdk,mcpAn ACP server running (Tip: Follow the ACP quickstart to start one easily)
An MCP client application (We use Claude Desktop in the quickstart)
Quickstart
1. Run the Adapter
Start the adapter and connect it to your ACP server:
uvx acp-mcp http://localhost:8000Replacehttp://localhost:8000 with your ACP server URL if different.
docker run -i --rm ghcr.io/i-am-bee/acp-mcp http://host.docker.internal:8000Tip: host.docker.internal allows Docker containers to reach services running on the host (adjust if needed for your setup).
2. Connect via Claude Desktop
To connect via Claude Desktop, follow these steps:
Open the Claude menu on your computer and navigate to Settings (note: this is separate from the in-app Claude account settings).
Navigate to Developer > Edit Config
The config file will be created here:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Edit the file with the following:
{
"mcpServers": {
"acp-local": {
"command": "uvx",
"args": ["acp-mcp", "http://localhost:8000"]
}
}
}{
"mcpServers": {
"acp-docker": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/i-am-bee/acp-mcp",
"http://host.docker.internal:8000"
]
}
}
}3. Restart Claude Desktop and Invoke Your ACP Agent
After restarting, invoke your ACP agent with:
use "echo" agent with the "Good morning!" inputAccept the integration and observe the agent running.


ACP agents are also registered asMCP resources in Claude Desktop.
To attach them manually, click the Resources icon (two plugs connecting) in the sidebar, labeled "Attach from MCP", then select an agent like acp://agents/echo.
How It Works
The adapter connects to your ACP server.
It automatically discovers all registered ACP agents.
Each ACP agent is registered in MCP as a resource using the URI:
acp://agents/{agent_name}The adapter provides a new MCP tool called
run_agent, letting MCP apps easily invoke ACP agents.
Supported Transports
Currently supports Stdio transport
Developed by contributors to the BeeAI project, this initiative is part of the Linux Foundation AI & Data program. Its development follows open, collaborative, and community-driven practices.
This server cannot be deployed
Maintenance
Related MCP Connectors
The Remote MCP server acts as a standardized bridge between LLM applications (like Claude, ChatGPT, and Cursor) and external services, enabling AI agents to access external tools and resources. Its primary capability is providing a centralized search tool to discover other MCP servers and their respective tools. Unlike local implementations, it runs remotely with OAuth authentication and permission controls for security.
AI agent registry — search, discover, register, and connect agents via MCP.
- QuallaaOAuthcom.quallaa
Talk to your public-facing AI from any MCP client — Claude, ChatGPT, Cursor, Cline, Windsurf.
Discover and call AI agents via MCP. Supports A2A agents and platform agents with async tasks.
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