Casefile

The task tracker your AI agents keep for each other.

Every task carries a case file — decisions, failed attempts, findings, open questions — so the next agent, with a fresh context and zero memory, picks up exactly where the last one stopped. You watch it all on a live board.

Install on macOS / Linux

curl -fsSL https://raw.githubusercontent.com/azimov777/casefile/main/install.sh | sh

Install on Windows (PowerShell)

irm https://raw.githubusercontent.com/azimov777/casefile/main/install.ps1 | iex

All you need is Docker. The board opens at http://localhost:8080, and the installer prints the one command that connects your agent. Casefile updates itself every time Docker starts.

Or let your agent do it. Paste this into Claude Code, Codex or Cursor:

Install Casefile for me by following https://raw.githubusercontent.com/azimov777/casefile/main/docs/agent-install.md

Why

Agents are smart, but they forget. A session ends or the context fills up, and the next one starts from scratch: re-reading the code, re-trying what already failed, re-asking what you already answered.

Casefile gives every task a case file — an append-only log the agent writes as it works.

• Hand-offs that survive a fresh context. The next agent reads the latest summary, the open questions and an index of the case, then carries on. No re-discovery.

• Built for agents, over MCP. Agents create and split tasks, record decisions and dead ends, ask you questions, and close with a verdict on every check.

• You stay in the loop. A live board and task pages show what every agent is doing. Answer questions, leave remarks and hand each agent its own access — right from the browser.

• Guardrails, not bureaucracy. No closing without a summary and a passed verdict per check; no starting a blocked task. Nothing else — no sprints, no estimates, no automation.

• Yours, on your machine. Runs locally in Docker and listens on localhost only. Nothing leaves your computer.

Related MCP server: roadmap-skill

Connect your agent

The installer prints a ready-made command with your token and its actual MCP address filled in — by default:

claude mcp add --transport http --scope user casefile http://localhost:8100/mcp \
  --header "Authorization: Bearer <token>"

Any other MCP client works the same way: streamable HTTP at the MCP address the installer printed (http://localhost:8100/mcp by default) with that header.

A second agent, without the terminal. The board carries the same snippets. Connect an agent shows this installation's MCP address and ready-made snippets for Claude Code, Codex and any client that takes an mcpServers JSON — no secret on the screen, a placeholder where the token goes. Access lists every token the installation has: who it speaks for, what it opens, who issued it and when it was last used. From there you register an agent, issue its own token, copy the snippet with the secret already in it — shown once — and revoke it when that agent is done. Give each agent a token of its own and its case entries are signed with its name instead of one shared agent.

For the best case files, also give your agent the skill that teaches the discipline (Claude Code: ~/.claude/skills/tracker-agent/SKILL.md).

Everyday

Ports and other settings live in ~/casefile/.env — see .env.example.

Under the hood

Python 3.14 · FastAPI · PostgreSQL · MCP over streamable HTTP · React 19 · Vite · Tailwind. The backend sits at the repository root, the web UI in ui/. The web UI speaks English and Russian; the design docs, the developer guide and the agent-facing texts are in Russian for now.

Contributing

Issues and pull requests are welcome — start with CONTRIBUTING.md. Commits need a sign-off (git commit -s): it certifies you have the right to submit the code, and CI checks it.

License

MIT

Hiring? I built Casefile and would be glad to hear about roles at Anthropic or OpenAI — reach me through GitHub.