INDIVIDUAL MCP TOOL

forget

Delete DURABLE MEMORY.

huggingbay.xyznone authenticationAvailability not checked

LIVE ENDPOINT

https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp

No auth detected

Connect to this endpoint to inspect the live schema for forget and invoke it with your own arguments.

{}

Potential side effects detected · medium confidence · heuristic, not a guarantee.

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.bay-run]
url = "https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "bay-run": {
      "type": "http",
      "url": "https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: bay-run
Remote MCP URL: https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "bay-run": {
      "url": "https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "bay-run": {
      "type": "http",
      "url": "https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "bay-run",
  "transport": "streamable-http",
  "url": "https://bay-run-mvp-zfmlsu2yla-uc.a.run.app/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

discover_models — Search a 147K-model catalog for a small, cheap, open specialist model that does ONE narrow job better/cheaper than a general LLM — embeddings, reranking, text classification, NER/extraction, routing, guardrails, transcription, vision, audio.
eval_models — Prove which candidate model actually wins on YOUR data before committing — a head-to-head bake-off, not a public leaderboard (MTEB rank does NOT predict your-domain performance).
embed — Turn text into embedding vectors using ANY open embedding model, served instantly on demand — no packaging, no deploy, no GPU.
rerank — Reorder candidate documents by true relevance to a query using an open cross-encoder/reranker, served instantly on demand — the standard move to sharpen RAG / search precision after a vector search returns a noisy top-k.
extract — Turn messy HTML/text (e.
find_specialist_for_task — ONE call to find the best small specialist model for your task, proven on YOUR examples.
route — RUNTIME auto-router: send a job WITHOUT knowing which specialist to use, and Bay Run picks the best mirrored specialist per-request at inference time.
classify — Classify text with a small CPU-served text-classification specialist — the guardrail / safety / moderation / sentiment / intent / NLI layer agents need and that frontier routers don't offer as tiny models.