Coordinating multiple AI coding agents on one repo or multiple in your own ecosystem — without git worktrees

说明与用途

多个 AI 助手在同一仓库中并行编辑时可能会发生冲突。解决方案是本地 WebSocket 中枢 SYNAPSE CHANNEL，管理文件声明、共享任务计划和轮询式协作，消除冲突并提升协作可靠性。

问题

Multiple AI coding agents editing the same repository concurrently cause file conflicts and lost work.

结果

Agents avoid file conflicts, maintain a shared plan, and coordinate turns without a central orchestrator, improving reliability and developer productivity.

工作流

• Install Synapse Channel hub: pip install synapse-channel synapse-hub --port 8876 --db ./synapse.db
• Each agent connects to the hub: agent = SynapseAgent("backend", uri="ws://localhost:8876")
• Agent claims file paths before editing: await agent.claim("auth-refactor", paths=["src/auth.py","src/session.py"])
• Use command-line to declare and update tasks: synapse task declare BUILD --title "compile", synapse task update BUILD --status done
• Agents wait for messages: synapse wait --name backend-rx --for backend --directed-only
• Send directed messages: synapse send --target backend "rebased main, re-pull"
• Wrap critical operations with a lease: synapse lock myrepo:git -- git push
• Hub persists state in SQLite; on restart it replays logs to resume leases and tasks.

证据

The hub refuses an overlapping claim. The hub never reads your filesystem — the globs are agent-declared.

来源

Every claim, release, task, and checkpoint goes into an append-only SQLite log and is replayed on start-up, so a hub restart resumes live leases instead of dropping them.

来源