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AgentWeave

A collaboration framework for N AI agents — Claude, Kimi, Gemini, Codex, Minimax, GLM, and more.

AgentWeave lets multiple AI agents work together on the same project through a shared protocol. The AgentWeave Hub is a self-hosted server with a web dashboard — the recommended way to run it.

Quick Start

Get up and running in 5 minutes:

# 1. Install the CLI
pip install "agentweave-ai[mcp]"

# 2. Start the Hub
agentweave hub start

# 3. Initialize your project
cd /path/to/your-project
agentweave init --project "My App"

# 4. Activate (connects Hub, sets up MCP, starts watchdog)
agentweave activate

See the Getting Started guide for full details.


What is AgentWeave?

AgentWeave solves a simple but important problem: how do you get multiple AI agents to collaborate on the same codebase?

It provides:

  • A shared protocol — tasks, messages, and context files that all agents can read and write
  • Multiple transport modes — local filesystem, git orphan branch, or HTTP via the Hub
  • An MCP server — native tool integration so agents can send messages and manage tasks autonomously
  • A web dashboard — real-time visibility into agent activity, tasks, and messages

Three Modes of Operation

Mode Setup Best For
Hub Docker + HTTP transport Teams, multi-machine, web dashboard (recommended)
Zero-relay MCP agentweave mcp setup + watchdog Autonomous loops, same machine, no server
Manual relay Zero setup Quick one-off delegation

Documentation

Section Description Links
Getting Started Install the CLI, start the Hub, and connect your first agents Installation · Quick Start
Guides Step-by-step guides for common tasks and workflows Adding New Agents · Context Files · Session Modes · AW-Spec Workflow · AI Jobs · Pilot Mode · Dashboard · FAQ
Reference CLI commands, MCP tools, API endpoints, and configuration options CLI Commands · MCP Tools · Task Lifecycle · Hub API
Architecture Understand how AgentWeave works under the hood Overview · Transport Layer · Messaging · Locking
Contributing Development setup and release process Development · Release Process

Dashboard Features

Open http://localhost:8000 to see:

  • Mission Control — centralized overview of session status and activity
  • Tasks board — all tasks with status, priority, assignee, and deliverables
  • Messages feed — inter-agent messages with inline task linking
  • Human questions — answer agent questions directly in the UI
  • Agent activity — live event stream, per-agent output logs, and session management
  • Agent chat — per-session chat history with session selector
  • Agent cards — connected agents with multi-role badges, yolo mode, and runner type

See Using the Dashboard for more.