Loading…
Workflow engine for executing Model Context Protocol (MCP) workflows. It provides a lightweight runtime for running AI-powered tasks across MCP-compatible servers with built-in support for authentication, resources, and tools. This package powers the Jotsu platform but can also be used independently in any Python environment.
jotsu-mcp is an MCP server entry in ChatHome Skills, sourced from GitHub MCP Search and scored 39/100. Workflow engine for executing Model Context Protocol (MCP) workflows. It provides a lightweight runtime for running AI-powered tasks across MCP-compatible serve. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding jotsu-mcp to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
git clone https://github.com/getjotsu/jotsu-mcp.gitReview the upstream source before running this command.
Scan coverage: Install metadata and repository README.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
{
"fullName": "getjotsu/jotsu-mcp"
}Workflow engine for executing Model Context Protocol (MCP) workflows. It provides a lightweight runtime for running AI-powered tasks across MCP-compatible servers with built-in support for authentication, resources, and tools. This package powers the Jotsu platform but can also be used independently in any Python environment.