open-multi-agent-canvas

The open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research

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README
Open Multi-Agent Canvas

CopilotKit-Banner

multi-agent-canvas

Open Multi-Agent Canvas, created by CopilotKit is an open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation. It's built with Next.js, LangGraph, and CopilotKit to help with travel planning, research, and general-purpose tasks through MCP servers.

Existing Agents

Check out these awesome agents (they live in separate repositories). You can run them separately or deploy them on LangSmith:

Additionally, this project now includes a built-in MCP (Multi-Channel Protocol) Agent:

  • MCP Agent: A general-purpose agent capable of handling various tasks through configurable MCP servers.
Copilot Cloud is required to run this project:
Quick Start 🚀
1. Prerequisites

Make sure you have:

2. API Keys
Running the Frontend

Rename the example.env file in the frontend folder to .env:

NEXT_PUBLIC_CPK_PUBLIC_API_KEY=...

Install dependencies:

cd frontend
pnpm i

Need a CopilotKit API key? Get one here.

Then, fire up the Next.js project:

pnpm run build && pnpm run start
MCP Agent Setup

mcp-demo

The MCP Agent allows you to connect to various MCP-compatible servers:

  1. Configuring Custom MCP Servers:

    • Click the "MCP Servers" button in the top right of the interface
    • Add servers via the configuration panel:
      • Standard IO: Run commands locally (e.g., Python scripts)
      • SSE: Connect to external MCP-compatible servers (via Server-Sent Events)
  2. Public MCP Servers:

Running the MCP Agent Backend (Optional)

Rename the example.env file in the agent folder to .env:

OPENAI_API_KEY=...
LANGSMITH_API_KEY=...

If you want to use the included MCP Agent with the built-in math server:

cd agent
poetry install
poetry run langgraph dev --host localhost --port 8123 --no-browser
Running a tunnel

Add another terminal and select Remote Endpoint.
Then select Local Development.
Once this is done, copy the command into your terminal and change the port to match the LangGraph server 8123
image

Documentation
License

Distributed under the MIT License. See LICENSE for more info.