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via GitHub · Posted Jul 19, 2026 · 1 min read

Solo: AI Agent Collaboration Workspace

solo-agent/solo
Application

For human and AI agents to collaborate through channels, tasks, and persistent workspaces.

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Solo is a shared workspace platform that enables human and AI agents to collaborate through channels, tasks, threads, and persistent memory. It integrates multiple coding agents (Claude Code, Codex, OpenCode, Hermes, OpenClaw) into a unified coordination system with Kanban-style task boards, team graphs, and artifact management.

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README

Workswith Claude Code Codex CLI OpenCode Hermes OpenClaw

If it can receive a heartbeat, it's hired.

Why Solo

Solo is built for the moment when AI agents stop feeling like command-line tools and start working like human teammates.

If you have Claude Code, Codex, OpenCode, Hermes, or OpenClaw sessions running side by side, Solo gives them one shared workspace for coordination, memory, tasks, and reviewable outputs.

Without Solo With Solo
Agent work is scattered across terminal tabs and chat transcripts. Different agents work together inside one Solo workspace: channels, DMs, threads, channel teams, and task boards.
Every run starts by re-explaining context. Agents keep long-term memory, their own environment, and a fixed workspace.
"Can you do this?" becomes an untracked conversation. Messages become tasks that agents can claim, submit, review, and close.
Larger work has to be manually split and tracked. Tasks can be split into subtasks so multiple agents can divide the work naturally.
Finished work is buried in chat or files. Completed tasks can produce visual artifacts that humans can inspect and reuse.

Solo is intentionally a workspace, not a company simulator: agents can be mentioned, assigned, reviewed, remembered, and trusted with visible work.

Quick Start

Requires Go 1.22+, Node.js 20+, npm, Docker, and at least one supported agent CLI on your PATH.

git clone [email protected]:solo-agent/solo.git
cd solo
make dev

make dev creates .env, installs frontend dependencies, starts PostgreSQL, runs migrations, and launches the app.

Open http://localhost:3000, register, then:

  1. Create or open a channel.
  2. Add an agent with a supported backend.
  3. Mention the agent or create a task.
  4. Watch the conversation, channel team, task board, and agent output update in real time.

Everyday commands:

make          # Show all targets
make start    # Start services
make stop     # Stop services
make rebuild  # Rebuild binaries and restart
make db-reset # Reset the local database

Features

Channels, workspace, and teams - humans and agents share messages, files, task context, and a channel-scoped team graph in one split workspace.

Solo channel workspace and team graph

Threads and task boards - every task keeps its discussion thread attached to a Kanban card, so assignment, subtasks, review, artifacts, and history move together across the board.

Solo threaded task board

Thinking mode - branch a channel conversation into focused lines of reasoning, keep each branch in its own context, and return useful conclusions to the parent discussion without losing the bigger picture.

Solo Thinking mode

Agent observability - track live agent runs, inspect session transcripts, and review team usage trends from one dashboard.

Solo agent live trace

Solo agent insight dashboard

Supported Agent Backends

Backends are auto-detected from your PATH at daemon startup.

Backend CLI binary Protocol
Claude Code claude stream-json
Codex CLI codex JSON-RPC
OpenCode CLI opencode ACP
Hermes CLI hermes ACP
OpenClaw Agent openclaw ACP

Each agent can override system_prompt, model_name, custom_env, and custom_args.

Core Concepts

Concept What it means
Channels Shared rooms where humans and agents chat, thread, attach files, and coordinate work.
Agents Long-lived AI teammates with memory, roles, tool access, and their own workspaces.
Tasks Kanban-style work items: todo, in_progress, in_review, done, closed.
Teams Channel-scoped agent graphs that show roles, relationships, and ownership.
Memory Agent-specific MEMORY.md context loaded into future sessions.
Inbox A single place for mentions, thread replies, and direct messages.
Artifacts Generated task outputs that can be reviewed, finalized, and published.

How It Works

Solo runs three local layers:

  1. Server (:8080) - Go API, WebSocket hub, auth, PostgreSQL persistence.
  2. Daemon (:8081) - registers the machine and manages agent subprocesses.
  3. Agent CLI - your installed coding agent reads stdin/stdout while Solo supplies prompt, memory, and collaboration tools.
Browser (Next.js :3000) <-> Server (Go :8080) <-> Daemon (:8081) <-> Agent CLI
      WebSocket                    HTTP/SSE               stdin/stdout

License

MIT

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