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ml-train

station__ml-pipeline__ml-train external (needs EXECUTION_BACKEND_URL) ml-pipeline non-pv Constructa Configa

Train a random forest model on labeled PV feature data. Returns model_id, training accuracy, AUC, F1 score, and feature importance rankings. Uses bagged decision trees with bootstrap sampling.

Taxonomy

Linnaean classification joined from the algovigilance taxonomy index via the parent config's rank.

Rank	Value
domain	`Substrata`
kingdom	`Constructa`
phylum	`Configa`
class	`station-config`
order	`ml`
family	`mcp-tool-config`

Characteristics:

substrate: config
domain: pv
lifecycle: continuous
authority: read
compounding: producer
io: agent-request → tool-response

Input schema

No inputs required.

Example call

POST /api/mcp
Content-Type: application/json

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "station__ml-pipeline__ml-train",
    "arguments": {}
  }
}

How to invoke from a client

From any MCP-aware client, add https://algovigilance.com/api/mcp as an MCP server, then call this tool by name. From a raw HTTP client, send the JSON-RPC body above to /api/mcp.

Agent-friendly formats

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All tools (3062 live)
/api/mcp — endpoint
/AGENTS.md — agent guide
/tools/ml-pipeline__ml-train/raw.md — this page's Markdown twin