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
What is Open Multi-Agent Canvas?
Open Multi-Agent Canvas is an open-source multi-agent chat interface that allows users to manage multiple agents in a single dynamic conversation, facilitating deep research and various tasks through MCP servers.
How to use Open Multi-Agent Canvas?
To use the Open Multi-Agent Canvas, you need to set up the frontend by installing dependencies, configuring API keys, and running the Next.js project. You can also connect to various MCP-compatible servers for enhanced functionality.
Key features of Open Multi-Agent Canvas?
- Manage multiple AI agents in one interface.
- Connect to various MCP servers for diverse functionalities.
- Built-in MCP Agent for general-purpose tasks.
- Easy setup with clear documentation.
Use cases of Open Multi-Agent Canvas?
- Travel planning with CoAgents Travel Agent.
- Conducting AI research with CoAgents AI Researcher.
- General-purpose tasks through the MCP Agent.
FAQ from Open Multi-Agent Canvas?
- Is Open Multi-Agent Canvas free to use?
Yes! It is open-source and free for everyone.
- What are the prerequisites for using this project?
You need to have pnpm installed and a Copilot Cloud API key.
- Can I run multiple agents simultaneously?
Yes! You can manage multiple agents in one conversation.
Open 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
The MCP Agent allows you to connect to various MCP-compatible servers:
-
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)
-
Public MCP Servers:
- You can connect to public MCP servers like mcp.composio.dev and mcp.run
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
Documentation
License
Distributed under the MIT License. See LICENSE for more info.
