GG

gobbyai/gobby

Developer tools

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22 stars 6 forks 품질 71 트렌드 30NOASSERTION

The bottleneck in AI coding isn't the model: It's the babysitting. Gobby is a local daemon that turns a task into a PR across Claude Code, Codex, Gemini, Qwen, and Droid.

개요

Gobby Start with a task. Walk away. End with a PR. That's the loop. Hand Gobby a task, walk away, come back to a PR. Behind that one command: a plan, an expansion into staged subtasks, isolated worktrees, dispatched agents, hook-time guardrails, validation, review gates, and a commit-linked close. If something goes off the rails, Gobby stops and escalates instead of merging garbage. 5K+ commits. 15K+ tasks across my projects. Two paying clients running production systems on it. The 0.4.x line was assembled through Gobby's own task, dispatch, review, and documentation flows — the receipts live in this repo's .gobby/tasks.jsonl. The bottleneck in AI coding stopped being model capability a long time ago. The bottleneck is babysitting. Agents lose context across compactions. They drift from the rules you wrote in your CLAUDE.md. They duplicate work. They burn thousands of tokens reloading the same MCP schemas every turn.

README

원문 README의 일부입니다. 원문 보기.

GobbyStart with a task. Walk away. End with a PR.


gobby build '#1842'

That’s the loop. Hand Gobby a task, walk away, come back to a PR.

Behind that one command: a plan, an expansion into staged subtasks, isolated worktrees, dispatched agents, hook-time guardrails, validation, review gates, and a commit-linked close. If something goes off the rails, Gobby stops and escalates instead of merging garbage.

Gobby built Gobby. 5K+ commits. 15K+ tasks across my projects. Two paying clients running production systems on it. The 0.4.x line was assembled through Gobby’s own task, dispatch, review, and documentation flows — the receipts live in this repo’s .gobby/tasks.jsonl.


Why this exists

The bottleneck in AI coding stopped being model capability a long time ago. The bottleneck is babysitting. Agents lose context across compactions. They drift from the rules you wrote in your CLAUDE.md. They duplicate work. They burn thousands of tokens reloading the same MCP schemas every turn. You still review every diff because you can’t actually trust what comes back.

The fix isn’t a better prompt. The fix is infrastructure around the agent.

Gobby is a local daemon that sits underneath the AI coding CLIs you already use — Claude Code, Codex, Gemini CLI, Qwen CLI, Factory Droid — and gives them what they’re missing: shared sessions, a durable task ledger, hook-time rules, progressive MCP discovery, agent isolation, review gates, and a build loop that turns a task into a PR without you in the middle.

It is not another agent. It is the control plane the agents you already have are missing.


What Gobby is

A Python 3.13+ daemon you run locally. PostgreSQL is the runtime hub database, configured from bootstrap database_url settings. HTTP and the installed web UI run on :60887, WebSocket on :60888, dev web UI on :60889, with a stdio MCP server that your coding CLIs talk to.

Three things make Gobby load-bearing:

GitHub에서 전체 README 보기

설치

uvx gobby --help
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설정

{ "mcpServers": { "gobby": { "type": "stdio", "command": "gobby", "args": ["mcp-server"] } } }