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title: hub-query-staging
emoji: 🔎
colorFrom: blue
colorTo: indigo
sdk: docker
app_port: 7860
short_description: Staging fast-agent MCP server for HF Hub queries.
hf_oauth: true
hf_oauth_expiration_minutes: 480
hf_oauth_scopes:
- inference-api
---
# hub-query-staging
This staging Space runs a raw-passthrough fast-agent MCP server backed by the custom Monty build used for Hugging Face Hub querying.
The deployed card uses `tool_result_mode: passthrough`, so tool results are returned directly rather than rewritten by a second LLM pass.
## Auth
This Space is configured for Hugging Face OAuth/token passthrough:
- `FAST_AGENT_SERVE_OAUTH=huggingface`
- `FAST_AGENT_OAUTH_SCOPES=inference-api`
- `--instance-scope request`
The README enables Space OAuth (`hf_oauth: true`) and the container sets the fast-agent OAuth environment. `SPACE_HOST` is used by fast-agent to derive the public OAuth resource URL. No shared `HF_TOKEN` is required for user-scoped OAuth/token pass-through.
Clients can either:
- send `Authorization: Bearer <HF_TOKEN>` directly, or
- use MCP OAuth discovery/auth flow
## Model
The deployed card uses:
- `hf.openai/gpt-oss-120b:sambanova`
## Main files
- `hf-hub-query.md` — raw MCP card
- `tool_entrypoints.py` / `monty_api/` — Hub query tool implementation
- `_monty_codegen_shared.md` — shared codegen instructions
- `wheels/fast_agent_mcp-0.8.0-py3-none-any.whl` — staging fast-agent wheel from `../fast-agent-pr/`
## Dependencies
The Space installs the staged `fast-agent-mcp` wheel from this repo and `pydantic-monty==0.0.17` from PyPI.
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