A task manager your AI agents keep themselves. Claude Code, Codex and Gemini CLI create, start and close their own tasks over MCP; hooks keep the board honest. Self-hosted, English and Russian.
A task manager your AI agents keep themselves. English · Русский
You work with Claude Code or Codex as usual and never mention a task manager. The agent creates the main tasks, takes them into work, marks what blocks it, completes them with a result and drops what you abandoned. After a session Conus shows what is in progress and what got done: who changed what, when and in which session, with the commits.
Conus tracks main tasks only: features, notable fixes, important bugs, decisions that lead to separate work. Small edits and the steps of an agent's plan never become tasks; they end up in the result of the main task.
"The agent keeps the tasks itself" takes three levels, each with its own mechanism:
Level Meaning Mechanism --------- 1. Access the agent can call the operations an MCP server and a REST API 2. Understanding the agent knows when to call them a protocol delivered by hooks, a skill and instructions 3. Reliability the board does not depend on the model's memory hooks on tool use and on stop, server-side reconciliation, a local outbox
On every agent machine conus-cli runs the agent's hooks and the conus mcp bridge. Hooks report facts (edited files, commits, test runs) and hand the agent a short snapshot of its open tasks at the start of a session and on every prompt. At the end of a turn the server checks the facts against the board and, when a main task was clearly left behind, asks the agent to update it. When the server is down, nothing stops: events wait in a local outbox and the agent keeps working.
From the project README.
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