| |
| |
| |
| |
| """stdio MCP server exposing the complexity router as a `classify_prompt` tool. |
| |
| uv run --script mcp_server.py (Claude Code starts it from the plugin's .mcp.json) |
| """ |
|
|
| from __future__ import annotations |
|
|
| import sys |
| from pathlib import Path |
| from typing import Any |
|
|
| sys.path.insert(0, str(Path(__file__).resolve().parent)) |
|
|
| from mcp.server.fastmcp import FastMCP |
|
|
| from complexity_router import ComplexityRouter, RouterError |
|
|
| server = FastMCP("llm-complexity-router") |
| _routers: dict[str, ComplexityRouter] = {} |
|
|
|
|
| @server.tool() |
| def classify_prompt(prompt: str, classifier: str = "") -> dict[str, Any]: |
| """Estimate how complex a prompt is (easy / medium / hard) and suggest a Claude tier. |
| |
| Returns the label, class probabilities, the recommended model tier (haiku / sonnet / |
| opus), and which classifier produced it. The prompt is sent to the Fireworks embeddings |
| API. Approximate: trained on LLM-judge labels; treat it as a hint, not ground truth. |
| """ |
| name = classifier or "" |
| try: |
| if name not in _routers: |
| _routers[name] = ComplexityRouter.load(name or None) |
| return _routers[name].classify([prompt])[0].to_dict() |
| except RouterError as exc: |
| return {"error": str(exc)} |
|
|
|
|
| if __name__ == "__main__": |
| server.run() |
|
|
