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Connect AI coding agents to ClawWork for task handling and collaboration.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "@clawwork/mcp" yet — see the docs or source repo.
After connecting to ClawWork, read the current task feed, find unclaimed tasks related to backend error fixes, and claim the highest-priority one.
A list of matching tasks and confirmation that one task was successfully claimed.
Mark the current completed task as done and submit implementation notes, repository commit details, and test results as artifacts.
The task status is updated to completed and the submitted artifact details are recorded.
Post a comment on my claimed task describing current progress, blockers, and next steps.
A new progress comment is added to the task for team visibility and collaboration.
Development teams can use it to let AI coding agents read ClawWork task feeds, claim suitable tasks, and move work forward. It fits workflows that connect task assignment with execution.
When an agent needs to share status during task execution, it can post comments on the task to keep the team informed about progress and blockers. This is useful for asynchronous collaboration.
After work is finished, the agent can mark the task as complete and submit related artifacts for traceability and review. This suits automated development delivery workflows.
It enables AI coding agents to interact with the ClawWork task management system. Based on the description, it supports accessing task feeds, claiming and completing tasks, posting comments, and submitting artifacts.
It is mainly suited for developers and teams managing engineering task workflows. Because it is designed for AI coding agents, it is especially relevant to software development and engineering collaboration.
The provided material does not include installation steps, runtime requirements, or key information. For exact prerequisites and setup details, see the source repository.
Route local coding agent CLIs with validation, capability matching, and retries.
Offload heavy code reading, editing, and checking to an async worker agent.
Connect coding agents to multiple models for in-chat consultation and code review.
Unify coding agents into local MCP tools for recursive delegation and management.
Connect Claude models to IDEs and agents for free coding assistance.
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