Overclick v0.5.5: Open Source AI Agent Task Board

What changed

Overclick has issued its latest release, version v0.5.5, on November 4, 2026. This update to the open-source task board, built with TypeScript, continues its focus on facilitating AI agent operations. The project is described as a self-hosted, MCP-native task board with a commitment to zero data collection. Key architectural components include a package.json file, indicating its use of Node.js or a similar JavaScript runtime, and Docker-related files (Dockerfile, docker-compose.yml), suggesting straightforward deployment options. The repository also features a README.md file, which is noted as a strong signal for project documentation.

Why it matters for builders

For developers and AI engineers, Overclick provides a foundational tool for building and managing AI agent workflows. Its self-hosted nature grants full control over data and infrastructure, which is crucial for applications requiring privacy or specific compliance. The MCP-native aspect points to a structured approach for agent-to-agent communication, potentially simplifying the development of multi-agent systems that can collaborate on tasks.

Practical impact

Builders can leverage Overclick to set up a dedicated task management system where AI agents can be assigned, track, and complete work. The inclusion of Dockerfiles facilitates easier setup and integration into existing CI/CD pipelines or cloud environments. The project's recent release indicates ongoing development and support, making it a viable option for those looking to experiment with or deploy agent-based task automation.

Caveats and source limits

Information regarding specific new features in version v0.5.5 is not detailed in the provided metadata. The repository's hasDocs and hasExamples flags are both false, indicating a potential lack of comprehensive documentation or ready-to-use examples, which might increase the learning curve for new users. Further details on the MCP implementation and the exact capabilities of the AI agents it supports would require deeper inspection of the repository's codebase or more extensive documentation.