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WebCodex

WebCodex gives ChatGPT, Claude, and other MCP clients a real development environment on machines you own, so an AI assistant can edit your actual repositories instead of a pasted snapshot. A self-hosted Server authenticates every request and routes it to a Runner sitting next to your code, where file edits, Git operations, test runs, shell commands, and long jobs execute with your real toolchain. Your projects never move into a hosted workspace; only the tool results you authorize travel back to the model. The browser Runtime Console shows project readiness, the work queue, session activity, and connected Runners, and it is where you decide pending approvals or accept and reject finished work, because the model cannot approve its own changes. Runners join with a short-lived pairing code and stay connected over QUIC, WebSocket, or polling, so machines behind NAT still work. One-command sharing opens a temporary session for a single repository, while durable setups run the Server and Runner as system services behind your own HTTPS domain. Workflow Sessions keep evidence and context across conversations, so long tasks survive closed browser tabs and threads you pick up days later. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

WebCodex
WebCodex
WebCodex
WebCodex
WebCodex

Benefits

  • Your Code Never Leaves
  • Repositories stay on the machines that already hold them; the Server cannot read Runner files directly, and only authorized tool results are returned to the AI client.
  • Real Toolchain, Real Results
  • Agents run your actual compilers, test suites, formatters, and Git checkout on the Runner host, so results match what you would get typing the commands yourself.
  • Humans Approve The Changes
  • The Runtime Console queues pending approvals, shows session evidence and diffs, and lets you accept or reject results, while the model can never accept its own work.
  • Works Across Your Machines
  • Runners pair with a short-lived code and reconnect over QUIC, WebSocket, or polling, so laptops, workstations, and servers behind NAT all join one durable setup.

Features

  • MCP And REST Surfaces
  • The Server exposes MCP for ChatGPT and Claude, a REST runtime API, and a GPT Actions OpenAPI schema over one authenticated boundary.
  • Runner Project Boundaries
  • Each Runner registers explicit project roots and executes file, Git, shell, and job operations only inside those boundaries with scoped credentials.
  • Runtime Console Review
  • The browser console at /console shows project readiness, work queues, session activity, and connected Runners, with approval and accept-or-reject actions.
  • Long-Running Job Support
  • Jobs keep running and stay observable beyond a single model turn, with evidence retained so work can be reviewed when it finishes.
  • Flexible Runner Transports
  • Runners connect outbound over QUIC, WebSocket, or polling with automatic fallback, authenticated by Runner tokens or shared keys per deployment.
  • Session Continuity Built In
  • Workflow Sessions save context and evidence so authorized work resumes across conversations, accounts, and browser windows without starting over.

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