Bay Run

Free OpenAI-compatible inference with signed provenance receipts and 3 focused MCP tools.

What does this entry provide?

Bay Run is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 73/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding Bay Run to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: Official MCP Registry
Quality: 73/100
Install method: streamable-http
Repo: barneywohl/bay-run
Repo updated: Aug 18, 2026

Install command

mcp add io.github.barneywohl/bay-run https://run.huggingbay.xyz/mcp/

Install method: streamable-http

Review the upstream source before running this command.

GitHub project Homepage

Quality

Repo stars

Repo updated

Aug 18, 2026

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.
Documentation (10) and description quality (10): parsed manifest or SKILL.md frontmatter, and a real description rather than a placeholder.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-08-18T00:58:50.767149Z",
      "publishedAt": "2026-08-18T00:58:50.767149Z",
      "statusChangedAt": "2026-08-18T00:58:50.767149Z"
    }
  },
  "server": {
    "name": "io.github.barneywohl/bay-run",
    "_meta": {
      "io.modelcontextprotocol.registry/publisher-provided": {
        "tools": [
          "get_task_quote",
          "run_task",
          "verify_result"
        ],
        "keywords": [
          "mcp",
          "llm-router",
          "small-models",
          "inference",
          "agents",
          "openai-compatible",
          "provenance"
        ],
        "categories": [
          "ai-and-machine-learning",
          "developer-tools",
          "agents"
        ],
        "llms_txt_url": "https://run.huggingbay.xyz/llms.txt",
        "quickstart_url": "https://run.huggingbay.xyz/quickstart",
        "oauth_token_url": "https://run.huggingbay.xyz/oauth/token",
        "server_card_url": "https://run.huggingbay.xyz/.well-known/mcp/server-card.json",
        "openai_compatible_base_url": "https://run.huggingbay.xyz/v1",
        "oauth_protected_resource_url": "https://run.huggingbay.xyz/.well-known/oauth-protected-resource"
      }
    },
    "title": "Bay Run",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "remotes": [
      {
        "url": "https://run.huggingbay.xyz/mcp/",
        "type": "streamable-http",
        "headers": [
          {
            "name": "Authorization",
            "isSecret": true,
            "isRequired": true,
            "description": "Mint the bounded launch bearer using the form-encoded client_credentials request shown at https://run.huggingbay.xyz/quickstart, then send Authorization: Bearer <token>."
          }
        ]
      }
    ],
    "version": "1.2.0",
    "repository": {
      "url": "https://github.com/barneywohl/bay-run",
      "source": "github"
    },
    "websiteUrl": "https://run.huggingbay.xyz",
    "description": "Free OpenAI-compatible inference with signed provenance receipts and 3 focused MCP tools."
  }
}

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