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Connect Hugging Bay

Add Hugging Bay's bounded open-model metadata tools to Claude, Cursor, Cline, OpenClaw, ChatGPT, or another MCP/OpenAPI-capable assistant.

Slash commands

Name the MCP server hugging-bay so commands read /mcp__hugging-bay__find-model-for-my-machine. List the seven commands with prompts/list; choose one and fill its arguments. Model names, memory and choices have completions. Commands guide tool use; request commands ask for your OK before submitting.

MCP (Claude Desktop / Claude Code / Cursor / Cline / OpenClaw)

{
  "mcpServers": {
    "hugging-bay": {
      "url": "https://huggingbay.xyz/api/mcp"
    },
    "bay-run": {
      "url": "https://run.huggingbay.xyz/mcp/"
    }
  }
}

hugging-bay supplies bounded public catalog metadata and evidence. bay-run supplies the separate specialist coprocessor; it does not proxy through Hugging Bay. Bay Run tool calls require its resource-bound OAuth bearer: compatible MCP clients follow the endpoint's protected-resource metadata automatically; otherwise mint the free MCP token through the Bay Run quickstart. Keep that token out of shared configuration files. The default Hugging Bay core profile exposes five read-only tools. Select profile=discovery for public plan, board and request tools. The separate public verify profile exposes additional verification tools; publisher/full remain authenticated, and full-profile access is never inferred from the presence of an Authorization header. Test: curl -s https://huggingbay.xyz/api/mcp -H 'Content-Type: application/json' -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

OpenAPI (ChatGPT Actions / custom GPTs / any HTTP agent)

Import the REST contract from https://huggingbay.xyz/openapi.json. Start with /api/agents/find-model, /api/agents/recommend-prose, /api/v1/artifacts/{id}/report.

Hosted-file metadata

Inspect explicit hosted-file rows through the bounded file inventory API.

Hugging Face mirror

Only hosted files resolve; others return 404. Clients do not automatically retry Hugging Face. To use Hugging Face for an unhosted repo, unset HF_ENDPOINT and rerun the command in a new process. Transformers needs all required config, tokenizer and weights files. Use hf download on current clients; huggingface-cli is for older installs. File availability does not prove a model will load.

Public metadata can lag privacy changes by about 5 minutes; every download is checked again.

HF_ENDPOINT=https://hf.huggingbay.xyz hf download <owner>/<name> <file>
HF_ENDPOINT=https://hf.huggingbay.xyz python3 -c 'from huggingface_hub import hf_hub_download; hf_hub_download("<owner>/<name>", "<file>")'
HF_ENDPOINT=https://hf.huggingbay.xyz huggingface-cli download Qwen/Qwen2.5-0.5B-Instruct-GGUF
HF_ENDPOINT=https://hf.huggingbay.xyz python3 -c 'from transformers import AutoModel; AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2", trust_remote_code=False)'
HF_ENDPOINT=https://hf.huggingbay.xyz llama-cli -hf <owner>/<name>:<quant>

Hugging Face download guide

Machine-readable guides

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