vllm-ops-mcp
Provides GPU/VRAM status monitoring via nvidia-smi for NVIDIA GPUs, including per-GPU memory usage and utilization, and per-process VRAM attribution (best-effort).
vllm-ops-mcp
Read-only ops/health MCP server for a local, WSL2/systemd-managed vLLM server -- liveness vs. real-completion health tiers, GPU/VRAM status, systemd service status, and live serve-flag introspection. Built to the same standard as mcp-factory and desktop-mcp, and other local tooling in this operator's portfolio: own pyproject, own fastmcp server, honest README, real test suite, no product code before a spec was confirmed.
This is not a container-lifecycle manager. It assumes vLLM already runs
as a bare-metal systemd unit inside WSL2 (this operator's actual setup --
see vllm-autostart), not inside Docker/Podman.
Quickstart
// ~/.claude.json (or any MCP-host stdio client config)
{
"mcpServers": {
"vllm-ops-mcp": {
"type": "stdio",
"command": "C:\\Users\\jaime\\projects\\vllm-ops-mcp\\.venv\\Scripts\\python.exe",
"args": ["C:\\Users\\jaime\\projects\\vllm-ops-mcp\\run_server.py"]
}
}
}Related MCP server: Local AI MCP
Tools (Phase 1 -- all read-only, no gating required beyond a throughput cap)
Tool | What it does | What it can't do |
|
| Cannot fix a degraded server -- reports ground truth only. |
|
| No detail beyond what vLLM's API itself exposes. |
| On-demand real completion with a caller-supplied prompt, for manual sanity checks. | Rate-limited (same bucket as |
|
| Per-process VRAM attribution does not work on this operator's actual WSL2 setup -- live-verified empty even while the vLLM process holds 13.7GB (see Limitations). Treat |
|
| Read-only -- cannot start/stop/restart the unit. No computed uptime duration (deliberately -- see Limitations, clock-discipline note). |
| Read-only launch-flag introspection. Prefers the LIVE process's actual argv ( | vLLM doesn't expose its own launch flags over the API, so this never queries the server itself -- it's always shelling out. Exec-script fallback parsing is best-effort shell-text parsing (less precise than the live-argv path). |
Future extension: restart_service (Phase 2, not built)
Deliberately not implemented in this release. Per the spec: vLLM is
shared infra other bots/tools depend on (options-bot, qwen_cli.py
callers, DeerFlow fallback), so a restart tool needs its own gating design
(off by default, VLLM_OPS_MCP_ENABLE_RESTART=1, refuse to touch a healthy
instance unless force=True, rate-capped) before it ships -- not
retrofitted onto a read-only MVP. Tracked as a v2 idea, not a current
capability. If built, it should wrap run-vllm.cmd's exact recipe (systemctl start vllm only, never blind stop/restart) rather than reinvent it.
The differentiator: probe HTTP, not the listener
Every health signal in this server comes from an actual HTTP request to the
OpenAI-compatible API (urllib.request, not a socket/connect check). This
is deliberate, not incidental: Get-NetTCPConnection and other
listener-based checks miss WSL2-mirrored-networking-relayed ports
entirely -- a genuinely healthy 127.0.0.1:8000 can be invisible to a
listener probe run from the Windows host. check-vllm.cmd already embodies
this lesson; this server generalizes it into two tiers (liveness vs. real
generation) that nothing else in this operator's fleet exposes as MCP tools.
Security
Read this before you register vllm-ops-mcp. Honesty about blast radius is the point.
This server shells out to
nvidia-smi,systemctl(viawsl -d), and reads/proc/<pid>/cmdline. All six tools are read-only -- nothing here starts, stops, restarts, or kills a process, and no tool accepts an argument that gets passed to a shell unescaped (unit/distro names come from server-side config, not caller input;shlex.quotewraps the one caller-adjacent path that does reach a shell string, the unit name insystemctl show).check_health(deep=True)andtest_completionfire a real inference call against a shared GPU server. Rate-limited (default 20 calls/min,VLLM_OPS_MCP_DEEP_RATE_LIMIT_PER_MIN) specifically because this vLLM instance is shared infra other bots/tools depend on -- a caller hammering this MCP could starve or slow other consumers even though every call individually looks "read-only."get_serve_config's live-process path reads/proc/<pid>/cmdline, which can include secrets if any were ever passed as CLI flags (none are, in this operator's actual setup -- the model path and flags are all non-secret; auth, if any, is environment-injected inside the exec script, not passed as an argv flag). Defense-in-depth: any argv entry whose preceding flag name matches a known-sensitive pattern (token,key,secret,password,passwd,credential--config. SENSITIVE_ARGV_FLAG_PATTERNS) has its value redacted to[REDACTED]before being returned, in both the structuredargv/flagsfields andraw_text; the flag name itself is left visible so the shape is still diagnosable. This applies across all three sources (live_process,exec_script,local_config_mirror).No tool has any write/mutate capability in this release. There is no env var that turns one on --
restart_servicedoesn't exist in this codebase yet (see Future extension above), so there's nothing to accidentally enable.
Honest-capabilities table
Claim | Implementation | Verified by |
Liveness health tier ( |
|
|
Deep/real-completion health tier |
|
|
Model list passthrough |
|
|
On-demand completion sanity check |
|
|
GPU/VRAM status via nvidia-smi |
|
|
Per-process VRAM attribution |
| Unit-tested with a mocked non-empty response; live-verified to return EMPTY on this operator's actual WSL2 setup -- see Limitations |
systemd unit status via structured |
|
|
Live-process launch-flag introspection via |
|
|
Exec-script fallback when the unit is down |
|
|
Local config-mirror override path |
|
|
Sensitive-flag-value redaction in |
|
|
Deep-inference rate limiting (shared-infra protection) |
|
|
WSL-vs-native shell-out abstraction |
|
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All 6 tools registered, no Phase-2 tool present |
|
|
Limitations (read before relying on this)
Per-process VRAM attribution is unreliable under this operator's actual WSL2 GPU-passthrough config.
get_gpu_status's live smoke test (realnvidia-smi.exeagainst the real running vLLM process) returned an emptyprocesseslist even though the same call'sgpus[0]. memory_used_mibcorrectly showed 13.7GB in use by that process. This is a documentednvidia-smi --query-compute-appslimitation under some WSL2/passthrough configurations, not a bug in this server's parsing -- the tool reports the empty result honestly (ok: true, processes: []) rather than fabricating attribution. Don't rely onprocessesfor VRAM-overshoot root-causing on this setup;gpus[].memory_used_mibis the reliable signal.No computed service uptime.
get_service_statusreturns the rawActiveEnterTimestampstring fromsystemctl(already timezone-labeled, e.g.MDT) rather than computing an elapsed duration server-side -- deliberately, per this operator's own clock-discipline rule (never state an elapsed/ETA time from estimation; artifact timestamps are often UTC while local is UTC-6/-7). Compute the delta at the call site if you need it, with an explicit timezone conversion.get_serve_config's exec-script fallback is best-effort shell-text parsing, not an exact argv array -- it handles\line continuations and basic quoting viashlex.split, but a sufficiently unusual exec script could parse incorrectly. The live-process path (/proc/<pid>/ cmdline) does not have this limitation (it's the kernel's exact argv, null-separated) and is always preferred when the unit is up.WSL2-specific by default, but the seam is explicit.
get_service_statusandget_serve_config's live-process path assume this server runs on the Windows host and shells into WSL2 viawsl -d <distro>. SetVLLM_OPS_MCP_RUNS_IN_WSL=1if this server process itself runs inside WSL2/Linux natively (nativesystemctl/cat, nowsl -dhop) -- both paths are unit-tested (TestGetServiceStatus::test_uses_wsl_prefix_on_windows/test_no_wsl_prefix_when_native), but only the Windows-host path has been live-verified against this operator's actual setup.Single vLLM instance, single GPU, this operator's setup. No multi-instance/multi-GPU aggregation;
get_gpu_statusreturns whatevernvidia-smi --query-gpuenumerates, which is every GPU visible to the process, not scoped to "the GPU vLLM is using" if more than one exists.No lifecycle control whatsoever in this release. See "Future extension" above -- this is intentional, not an oversight.
Env vars
Var | Effect | Default |
| OpenAI-compatible base URL |
|
| served-model-name, used in completion payloads |
|
| WSL distro hosting vLLM |
|
| systemd unit name |
|
| WSL-side path to the serve exec script (fallback source) |
|
| local file mirror of the exec script; if set, | unset |
|
|
|
|
| auto-detected via |
| cap on |
|
|
| unset (skip) |
Usage examples
// A tool call from the MCP host, illustrative -- not a shell command.
{"tool": "check_health", "arguments": {"deep": true}}
// -> {"ok": true, "status": "up", "tier": "deep", "model_id": "qwen3-14b",
// "latency_ms": 32.0, "completion_s": 0.218, "error": ""}
{"tool": "get_serve_config", "arguments": {}}
// -> {"ok": true, "source": "live_process", "pid": 5645,
// "flags": {"model": "Qwen/Qwen3-14B-AWQ", "served_model_name": "qwen3-14b",
// "port": "8000", "max_model_len": "8192",
// "gpu_memory_utilization": "0.72", "max_num_seqs": "8",
// "enable_auto_tool_choice": true, "tool_call_parser": "qwen3_xml", ...}}
// rate limit exceeded (21st deep call within a minute):
{"tool": "test_completion", "arguments": {"prompt": "hi"}}
// -> {"ok": false, "error": {"type": "rate_limited", "group": "deep_inference",
// "tool": "test_completion", "limit_per_min": 20, "retry_after_s": 4.87}}Testing
CI (.github/workflows/ci.yml) runs this suite on every push/PR (ubuntu-latest --
the unit suite mocks HTTP/subprocess, no live server/GPU/WSL required) and
fails the build if the Tests badge above drifts from what the suite
actually reports -- see scripts/check_readme_counts.py.
# unit suite (mocked HTTP/subprocess, no live server/GPU/WSL required)
.venv\Scripts\python.exe -m pytest -q
# -> 95 passed, 7 skipped
# handshake check -- prints every registered tool name
.venv\Scripts\python.exe scripts\list_tools.py
# real-infra smokes (real vLLM completion, real nvidia-smi, real systemctl
# via WSL, real /proc/<pid>/cmdline read) -- read-only, safe to run anytime
# vLLM is up
VLLM_OPS_MCP_LIVE=1 .venv\Scripts\python.exe -m pytest -v -m live
# -> 7 passed (all live, against the actual running qwen3-14b instance)Install
python -m venv .venv
.venv\Scripts\python.exe -m pip install -r requirements.txtRegistered in ~/.claude.json as vllm-ops-mcp (stdio, own .venv, no env
overrides needed for this operator's default setup).
Commercial support
Maintained by Jaimen Bell. For production MCP integrations, custom servers, or agent-reliability work, see jaimenbell.dev or sponsor ongoing maintenance via GitHub Sponsors.
mcp-name: io.github.jaimenbell/vllm-ops-mcp
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