AgentsMesh
Orchestrate isolated terminal coding agents across your own machines from one control plane.
What does this agent do, and when should you use it?
AgentsMesh is a self-hosted execution and orchestration platform for AI coding agents. Its Go services comprise Backend, Relay, and Runner: Runner executes isolated AgentPods on user machines, Backend manages identity, scheduling, tickets, and runner certificates, and Relay carries live terminal traffic. Each pod has a separate Git worktree, branch, private credentials, and PTY, reducing interference between concurrent tasks. Web, Electron desktop, and iOS clients share a Rust business-logic core and expose terminals, multi-pane workspaces, Kanban tickets, and collaboration topology. The platform supports Claude Code, Codex CLI, Gemini CLI, Aider, OpenCode, and other terminal-based agents; it documents both a Docker-based local stack and self-hosted deployment guidance.
An operator creates an AgentPod from the Web, Desktop, or iOS console, and AgentsMesh schedules it to a chosen or available self-hosted Runner. The Runner connects to Backend through gRPC with mTLS, creates an isolated Git worktree sandbox at sandboxes/{pod}/workspace/, provisions a branch, private credentials, and a PTY, then runs a terminal-based coding tool. Terminal bytes flow through the stateless Relay WebSocket data plane to clients, while Backend manages pod lifecycle, organizations, users, tickets, billing, and runner PKI. Pods can be linked through Mesh and Channel, where they communicate using @mentions; Autopilot sends a next instruction when a pod becomes idle and retains iteration and decision history.
- An engineering lead maintaining several repositories can install Runners on internal machines and dispatch parallel fixes, tests, and implementation tasks to separate pods.
- A development team that uses Claude Code, Codex CLI, and Gemini CLI can launch and observe those terminal tools from one console.
- A developer who cannot risk concurrent agents changing the same checkout can assign each task to its own Git worktree, branch, and credentials.
- A solo operator running long unattended coding jobs can use Autopilot to continue an idle pod, while retaining the option to take over manually.
- A team managing engineering work on a Kanban board can bind a Ticket to a pod and follow its progress and MR/PR status.
What are this agent's strengths and limitations?
- Runners can be installed across multiple user-owned machines, keeping code in the user's infrastructure while scheduling pods by capacity.
- Each pod receives a dedicated Git worktree, branch, PTY, and private credentials, which directly isolates concurrent coding work.
- The architecture separates orchestration from terminal transport: Runner-to-Backend control uses gRPC with mTLS, while stateless Relay handles terminal streaming.
- A shared Rust business-logic core serves Web, Electron, and iOS clients, while the built-in agent list spans several terminal coding tools.
- The full local development stack explicitly requires Go 1.24+, Node.js 20+, pnpm, and Docker, adding operational overhead compared with a standalone CLI.
- Runner authentication uses a browser flow; headless environments need the separate `--headless` login path.
- The hosted workflow requires Git-provider connection and BYOK, leaving model API costs and key management with the user.
- The repository is licensed under BSL-1.1; its README states that production use requires a commercial license until the change date.
How do you install or deploy this agent?
For the hosted path, run curl -fsSL https://agentsmesh.ai/install.sh | sh on each target machine, then run agentsmesh-runner login. On a headless machine, use agentsmesh-runner login --headless; for a self-hosted server, add --server https://your-server.com. After authentication, provide your own AI API keys (BYOK) and run agentsmesh-runner run to bring the machine online as a Runner. For local development, run git clone https://github.com/AgentsMesh/AgentsMesh.git, change to AgentsMesh/deploy/dev, and run ./dev.sh; the documented prerequisites are Go 1.24+, Node.js 20+, pnpm, and Docker.
How do you use this agent?
Once a Runner is online, create an AgentPod in a Web, Desktop, or iOS console and either select a Runner or allow scheduling from the available pool. Choose an installed terminal-based tool such as Claude Code, Codex CLI, Gemini CLI, Aider, or OpenCode, assign work, and watch its terminal stream from the pod workspace. For an always-on Runner, run agentsmesh-runner service install followed by agentsmesh-runner service start. After the local development stack starts, the Web Console is at http://localhost:3000 and the API is at http://localhost:80/api; check deploy/dev/.env for actual dynamically allocated ports.