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Run iterative AI coding tasks on repositories with quality, security, and approvals.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ForLoop MCP" yet — see the docs or source repo.
Run an iterative fix workflow on this repository: identify failing tests, modify the code step by step, and rerun tests each round; include quality evaluation and security checks, and only propose changes after all gates pass.
Provides root-cause analysis, per-iteration change logs, final test-passing code suggestions, and quality and security check results.
Implement a new feature based on the existing repository structure: inspect relevant modules first, then code in steps, add tests, and validate iteratively; if risks are detected, trigger security gates and wait for approval before continuing.
Delivers an implementation plan, code changes, supporting tests, risk notes, and final recommendations after approval checkpoints.
Refactor selected modules in the repository: iteratively perform refactoring, static analysis, test validation, and security review without changing behavior, then summarize each step.
Returns refactored code suggestions, behavior consistency validation results, quality score changes, and security review conclusions.
Detect retry loops and iteration patterns to improve debugging and repair attempts.
Orchestrate tasks as a DAG with validation loops and iterative fixes
Review code, suggest refactors, and generate tests with AI assistance.
Inspect legacy repos and set up better Copilot guidance foundations.
Continuously mines and improves AI agent workflows for self-improving execution loops.
Turn plain-English goals into verified, looped, observable IDE agent build runs.