Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@AI Engineering Agent — Repository Inspector scan this repo for TODOs and FIXMEs and show the largest files"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A read-only developer tool with two MCP tools: repository inspection and log analysis. It returns JSON reports and keeps MCP access inside a configured workspace. Model-backed reasoning is a future extension; the current analysis is deterministic.
python inspect_repo.py /path/to/repository --output report.json
python inspect_repo.py .
python analyze_log.py examples/sample.logThe standalone CLIs use Python 3.10+ and have no third-party dependencies. The repository tool counts source files, reports the largest files, and collects a capped list of TODO and FIXME comments. The log tool counts warning and error lines. Both are read-only.
Related MCP server: Convorel
python -m pip install -r requirements.txt
python server.pyConfigure your MCP client to launch python server.py over stdio, with ENGINEERING_ROOT set to the repository or workspace you want it to inspect. The server exposes inspect_repository(path) and analyze_log_file(path). Relative paths resolve from that root; paths outside it are rejected. The default root is the server's current working directory.
The server waits for an MCP client on standard input; it does not print a startup page.
Run python -m unittest discover -s tests -v to exercise both tools, including an in-process MCP call. GitHub Actions runs these checks on each push.
{
"root": "/absolute/path/to/repository",
"files_scanned": 12,
"extensions": {".py": 8, ".md": 4},
"largest_files": [],
"markers": []
}The values above illustrate the response shape; they are not a measurement of this repository.
MCP client -> workspace boundary -> bounded scan -> JSON reportThe repository scan is bounded to 1,000 files, 1 MiB per file, and 50 markers. Log analysis reads at most 1 MiB and returns at most 20 matching lines. Neither tool runs code or shell commands from the target repository. Future milestones include optional model summaries and workflow execution with explicit controls.
MIT
This server cannot be deployed
Run verified read-only code tools: quant diagnostics + agent-ops preflight, no source exposure.
Generate SBOMs, scan vulnerabilities, and analyze dependencies from local projects or Git repos.
Review connected software projects, submit local findings and read reports with explicit approval.
Screens public GitHub repos and PRs to generate risk maps, findings, and merge-readiness signals.
