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Structured MCP tools for common developer operations and low-token JSON outputs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "swiss-knife" yet — see the docs or source repo.
Summarize the latest test run in the current project and return structured JSON with passed count, failed count, failed test names, and key details.
A structured test summary that makes test status easy to review and reduces context overhead.
Extract Git commit context from the current repository and return structured JSON with recent relevant changes, affected files, and notes useful for a commit message.
A JSON result describing change context and scope, ready for commit writing or code review preparation.
Wait until a specified condition is met, then return structured JSON describing the wait status and final result.
A structured output showing whether the condition was met, the wait status, and the final result.
Developers can use it to turn file outlines, commit context, and test results into structured JSON for AI workflows. This reduces unnecessary token usage in long conversations or automation pipelines.
When preparing a Git commit or code review, users can extract commit context and impacted scope first to build a clearer change summary. This helps reduce time spent manually inspecting repository state.
In local development or scripted workflows, users can summarize test results, manage processes, or wait for conditions to be met. It fits developer and DevOps scenarios that need programmatic outputs.
It provides MCP tools for common developer operations such as file outlining, Git commit context, test summaries, process management, and waiting for conditions. Results are returned as structured JSON to reduce token usage.
It is best suited for developers and also useful for people who need structured outputs in automation or DevOps workflows. Based on the description, it focuses on development-related tasks.
The provided material does not include installation steps, runtime requirements, or API key details. Please see the source repository for specifics.
Search MCP servers in a registry and add them to configuration.
Gives coding assistants repo status, commit, test, and lint checks.
Refactor code via MCP with moving, indenting, outlining, and renaming.
Analyze code structure and Git history while drastically reducing AI token usage.
Compress and proxy MCP responses to reduce token usage for LLM tool calls.
Run dev checks and get compact error summaries for faster debugging.