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실행게시자 제공
One MCP server. Your AI agent just learned forensics.
Zero dependencies · One file · The MCP framing is implemented by hand
MCP server that exposes the fernedy ops suite (container-autopsy, death-noticer, git-sins) as native tools for any MCP client.
You already have AI agents. What they don't have is your ops tooling.
ops-mcp is a Model Context Protocol server that exposes the fernedy ops suite as native tools for any MCP client — Claude Desktop, opencode, Cursor, or anything that speaks stdio JSON-RPC:
No glue code, no copy-pasting terminal output into a chat window. The agent calls the tool, gets the markdown report, and reasons over it.
git clone https://github.com/fernedy/ops-mcp.git
git clone https://github.com/fernedy/container-autopsy.git # sibling repos
git clone https://github.com/fernedy/death-noticer.git
git clone https://github.com/fernedy/git-sins.git
cd ops-mcp
python ops_mcp.py # MCP stdio server, ready for any client
Point your MCP client at it (Claude Desktop example):
{
"mcpServers": {
"ops-mcp": {
"command": "python",
"args": ["/path/to/ops-mcp/ops_mcp.py"]
}
}
}
The image is self-contained: it clones the three tool repos at build time.
docker build -t ops-mcp .
# clients must keep stdin open (-i): MCP speaks stdio
docker run --rm -i -v /var/run/docker.sock:/var/run/docker.sock ops-mcp
Or configure the client directly:
{
"mcpServers": {
"ops-mcp": {
"command": "docker",
"args": ["run", "--rm", "-i",
"-v", "/var/run/docker.sock:/var/run/docker.sock",
"ghcr.io/fernedy/ops-mcp:latest"]
}
}
}
container_autopsy(container, tail?) — full forensic workup of a dead (or running) container: evidence table, cause of death, contributing findings, the fix. Powered by container-autopsy.container_obituary(container) — a shorter, warmer goodbye: lifespan, cause of death, final words. Powered by death-noticer.git_sins(repo, share?) — a confession of any git repository: nine sins with evidence and penance, 0–100 Sin Score. Powered by git-sins.Everything is read-only: the server invokes the tool CLIs in their own repos (OPS_MCP_TOOLS_HOME, defaults to the parent directory). It never restarts, mutates or writes to your infrastructure.
This server is the AI-First layer: the deterministic tools stay the source of truth, and your agent becomes the interface that interprets and explains their reports. Human in the loop is unchanged — tools diagnose, humans act.
One Python file, zero dependencies. The MCP stdio framing (newline-delimited JSON-RPC 2.0: initialize, tools/list, tools/call, ping) is implemented by hand — read the source as the protocol documentation.
python -m unittest discover -v # 14 tests: real stdio handshake, real tool calls
The suite spawns the actual server process and speaks MCP to it, including a real git_sins call against a real temp repository. CI runs on Python 3.8, 3.10 and 3.12. See .github/workflows/ci.yml.
This is step 2 of a linear path: tools → MCP server → guard agent. Step 3 is an always-on agent that listens for container deaths, diagnoses them through this server and prepares the fix as a PR for human approval.
MIT — see LICENSE.
Built AI-first by Fernedy Arias · Tech Explorer
If ops-mcp made your agent actually useful at 3 AM, drop a ⭐.
MCP server that exposes the fernedy ops suite (container-autopsy, death-noticer, git-sins) as native tools for any MCP client.
도구
아직 도구 목록이 없습니다. 원격 서버는 첫 상태 확인 후에 도구 목록이 생깁니다.
FAQ
이 페이지에서 Cursor, Claude Desktop, Claude Code 또는 VS Code용 stdio 설정을 복사합니다. PlugMCP 프록시가 아니라 게시자의 설치 방식을 사용합니다.
이 레코드에는 필수 환경 변수가 등록되어 있지 않습니다.
Ops은(는) stdio를 통해 로컬에서 실행됩니다.
마지막 확인: 2026-10-28. MCP server that exposes the fernedy ops suite (container-autopsy, death-noticer, git-sins) as native tools for any MCP client.
