Hugging Face MCP Server is a Model Context Protocol server that connects language models and coding agents to the Hugging Face Hub and Gradio applications. Users install it in supported agent environments to access configured Hugging Face tools and Spaces. The catalogue instruction describes how to use this server.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add huggingface/hf-mcp-server --skill space-doctorgit clone --depth 1 https://github.com/huggingface/hf-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/huggingface/hf-mcp-server/space-doctor)<a href="https://agentmods.dev/skills/huggingface/hf-mcp-server/space-doctor"><img src="https://agentmods.dev/badge/skills/huggingface/hf-mcp-server/space-doctor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/huggingface/hf-mcp-server/space-doctor"><img src="https://agentmods.dev/badge/skills/huggingface/hf-mcp-server/space-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.01574 |
| Opus 5 | $0.00039 | $0.00787 |
| Sonnet 5 | $0.00016 | $0.00315 |
| Haiku 4.5 | $0.00008 | $0.00157 |
Grade A, and why
space-doctor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Space Doctor
Diagnose a broken Hugging Face Space and, when a narrow reversible source fix is appropriate, write the complete fixed files into the candidate directory you were given. You have no Hub write access: never attempt an upload, PR, restart, or any other mutation. The parent process opens a PR from your candidate files and performs any restart itself.
Use fast-agent for reasoning and Hub reads. Diagnose from the observed failure, actual Hub logs, and the pinned source; static patterns and generic automated rewrites are not a repair decision.
Scheduled contract
A scheduled request provides the Space ID, exact failing revision, run ID,
observed status/stage/detail, previous restart outcome for that revision (when
one exists), and a workspace containing a candidate/ directory. Treat the
restart outcome as evidence, not proof that the current failure has the same
cause. Emit exactly one final structured result matching the configured JSON
schema, only after all work is complete:
status: "fix-proposed"withchanged_files,fix_summary, andpr_titlewhen you have written complete fixed files (paths relative to the Space repository root) intocandidate/.status: "needs-human"withneeds_human_reasonotherwise.
Diagnose exactly the requested revision. If the Space has moved to a different
revision, report needs-human with reason revision-changed. Never place
credentials, tokens, or local filesystem paths in any output field.
Workflow
1. Inspect remote state
Prefer connected Hugging Face MCP tools. With the hf CLI:
hf spaces info <namespace/name> --expand runtime --format json
hf spaces logs <namespace/name> --tail 300
hf spaces logs <namespace/name> --build --tail 300 # for BUILD_ERROR
Record runtime stage, hardware, revision, runtime.raw.errorMessage, and the
first actionable error. Read both build and runtime logs when relevant and
compare them with the observed status/stage/detail supplied in the request.
Always use the full 40-character repository SHA. Do not treat RUNNING alone
as healthy.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 154 lines · 78 tokens per session scan A 7f396c3be187
space-doctor is a skill published in the GitHub repository huggingface/hf-mcp-server (294 stars, last pushed 3d ago), licensed MIT. It adds 78 tokens to every session and 1,574 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-08.
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