Clixad
Freemium
Developers who prefer terminal workflows
Two AI coding agents editing the same file at the same time is a silent disaster — no warning, no merge conflict, just one agent's work erasing the other's. Bothread exists to stop that from happening.
Bothread runs locally on your machine and coordinates MCP-compatible agents — Claude Code, Cursor, Gemini CLI, Codex, and others — on a single codebase through a shared room where agents claim files before editing them. You watch the live thread of agent activity and can pause, redirect, mute, or remove any agent mid-task. An optional approval gate lets you sign off before any action flagged as risky proceeds. The coordination layer calls no models itself and requires no API keys — it only manages the agents you are already running. The ceiling appears when your project requires agent tooling that does not speak MCP: any agent outside that protocol sits outside Bothread's coordination entirely.
Bottom line: Bothread is the right call when you are running two or more MCP-compatible agents on one codebase and want local-only coordination with no cloud dependency — it breaks down the moment any agent in your stack does not support MCP.
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More options in CLI Coding Agents. Compare pricing, platforms, and features side by side.
Freemium
Developers who prefer terminal workflows
Freemium
Developers preferring fully local agent execution
Running more than one AI coding agent on the same project without coordination is asking for overwritten files and invisible conflicts. Bothread addresses this by giving MCP-compatible agents — Claude Code, Cursor, Antigravity, Gemini CLI, Codex — a shared room on your local machine where they negotiate file access before any edit happens. An agent claims a file, does its work, and releases it; no other agent touches that file in the meantime. You watch every action in a live thread and hold controls to pause, redirect, mute, or remove any agent without stopping the others.
The differentiating detail is what Bothread does not do: it calls no models, stores nothing in the cloud, and requires no API keys or account. It runs on 127.0.0.1 and coordinates agents you already have configured. This means the tool adds zero marginal cost and zero new data exposure — the security and cost profile of your existing agents does not change. For teams with strict data-residency requirements or individuals who simply do not want another cloud dependency, that architecture is the whole pitch.
Bothread fits best when your agent stack is already MCP-native and you need a lightweight coordination layer to prevent the race conditions that appear once two agents are working the same project simultaneously. It breaks down when any agent you depend on does not support MCP — that agent cannot join the shared room and sits outside the conflict-prevention system entirely. At that point, teams either replace the non-MCP agent with a compatible alternative or accept that coordination is only partial. There is no plugin path or adapter layer described in the docs for bridging non-MCP tools.
Setup follows the MCP server pattern: add the Bothread server to each agent’s configuration, and the agent gains the ability to join a room. The project is MIT-licensed and hosted on GitHub, so the coordination logic is auditable. The getting-started page is at bothread.vercel.app/start.
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