Generate new code from a natural-language instruction using the local Ollama model.

Pass context_file (a server-side path) instead of pasting an existing file's contents to give the model style/API context without spending your own context window on it. Set think=False for faster, simpler generations; leave think=True for anything non-trivial.

Review code for correctness bugs, security issues, and simplification opportunities.

Provide exactly one of code (inline text) or file_path (a server-side path read directly by this tool, saving your context window). focus can narrow the review, e.g. "concurrency" or "input validation".

Refactor code according to an instruction, preserving external behavior.

Provide exactly one of code or file_path. Returns the full refactored code plus a summary of changes; this tool does not write files itself -- use batch_refactor if you want changes applied to disk.

Diagnose and fix a bug in code, given an optional error message or symptom.

Provide exactly one of code or file_path. Include error_message (a stack trace, test failure, or description of wrong behavior) whenever you have one -- it substantially improves fix quality.

Write tests covering the golden path and realistic edge cases for given code.

Provide exactly one of code or file_path. Set framework (e.g. "pytest", "jest") to match your project's conventions; otherwise the model infers one from the code's language.

Explain what code does, including control/data flow and non-obvious behavior.

Provide exactly one of code or file_path. Explanations are usually fast enough that think=False (the default) is sufficient.

Review a git diff (e.g. git diff main...HEAD) as if for a pull request.

Provide exactly one of diff (inline diff text) or diff_file (a server-side path to a saved diff). context can carry the PR description or any background the model should know.

Apply a refactor instruction to every file matching a glob pattern, sequentially.

glob_pattern matches relative paths under root_dir (default: the server's allowed base directory), e.g. "src/**/*.py". Files are processed one at a time against the local model. With dry_run=True (the default) nothing is written -- you get a unified diff per file to review first; set dry_run=False to write accepted changes to disk. Large match sets are capped (see OLLAMA_MCP_MAX_BATCH_FILES) to avoid runaway sequential runs.

Check connectivity to the configured Ollama host and report available models.

Call this first if other tools are failing, or proactively before a batch of delegated work, to confirm the local model is reachable and pulled before relying on it.