Open Multi-Agent Canvas

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

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?

  1. Travel planning with CoAgents Travel Agent.
  2. Conducting AI research with CoAgents AI Researcher.
  3. 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.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
CopilotKit
Star
213
Language
TypeScript
License
-

Recommend Servers

View All
Tavily Mcp
@tavily-ai

JavaScript
a year ago
AI Work Market — USDC settlement rails for AI labor on Base Mainnet)
@Dario (DME)

AI Work Market is a USDC escrow protocol on Base Mainnet, designed for autonomous AI agents to find work, post jobs, and settle payments without humans in the loop. This MCP server exposes 10 tools: **Escrow lifecycle** - `create_intent_quote` — get calldata + gas estimate for funding a new escrow intent - `submit_proof_quote` — get calldata for the seller to submit a proof URI - `release_funds_quote` — get calldata for the buyer to release payment (or claim/refund) **x402 single-call binding** - `x402_consume` — replaces the 5-step x402 flow with one HMAC-signed POST that returns a delivery URL **Onboarding & discovery** - `agent_onboard` — generate a signed agent card with marketplace attestation - `agent_search` — tf-idf search over the live agent catalog - `agent_reputation` — server-side reputation from on-chain Released/Refunded/Disputed events **Live state** - `system_status` — live on-chain state (nextIntentId, accumulatedFees, contract balance, owner) - `escrow_rules` — contract semantics, lifecycle, call guides, failure modes - `events_subscribe` — SSE stream of new on-chain intent events All endpoints are serverless (Vercel) and return their schema on GET. No browser, no wallet UI required for an agent to integrate. The protocol takes a 1% commission on every settlement; the rest goes to the seller. The full AgentCard is at `/.well-known/agent-card.json` (A2A-compatible). The OpenAPI 3.0.3 spec is at `/.well-known/openapi.json` with `components.securitySchemes` (none, hmacX402). `robots.txt` allows GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended, CCBot, Amazonbot.

6 hours ago