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c088eff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 | """Minimal reference implementation of the BioDesignBench MCP contract.
Submitters who want to evaluate their own tool implementations against
the BioDesignBench leaderboard can fork this file, plug in their own
logic for each tool, deploy it behind a public HTTPS URL, and paste
that URL into the submission form under "Advanced: Custom MCP".
The leaderboard's agent loop will POST each tool invocation to your
endpoint and treat the JSON response as the tool result. The MCP never
sees the raw task description or evaluation criteria — only the
operational arguments the agent chooses to pass (a protein sequence,
a PDB path, a set of hotspot residues, etc.).
Contract:
POST <your-url>/
Authorization: Bearer <optional shared token>
Content-Type: application/json
{
"name": "<tool_name>", # one of the 17 tool names
"arguments": { ... } # per-tool JSON object
}
Response: arbitrary JSON object describing the tool output.
Errors should be reported in a top-level "error" field rather
than via HTTP status codes.
Install:
pip install fastapi uvicorn
Run (locally, with ngrok for a public URL):
uvicorn example_mcp_server:app --host 0.0.0.0 --port 8000
ngrok http 8000
Deploy (Modal example):
modal deploy example_mcp_server.py # see bdb-boltz as a template
Tool name list (17 total) — the full JSON Schema for each lives in
`mcp_tool_schemas.json` in this repo:
design_binder, analyze_interface, validate_design, optimize_sequence,
suggest_hotspots, get_design_status, predict_complex, predict_structure,
score_stability, energy_minimize, generate_backbone, rosetta_score,
rosetta_relax, rosetta_interface_score, rosetta_design,
predict_structure_boltz, predict_affinity_boltz
"""
from __future__ import annotations
import os
from typing import Any
from fastapi import FastAPI, Header, HTTPException
from pydantic import BaseModel
app = FastAPI(title="BioDesignBench MCP (example stub)")
SHARED_TOKEN = os.environ.get("BDB_MCP_TOKEN", "")
class MCPRequest(BaseModel):
name: str
arguments: dict[str, Any] = {}
# ---------------------------------------------------------------------------
# Tool handlers (REPLACE THESE STUBS WITH YOUR ACTUAL IMPLEMENTATIONS)
# ---------------------------------------------------------------------------
def handle_predict_structure(args: dict) -> dict:
"""Predict the structure of a single protein sequence.
Real implementations would call AlphaFold2, ESMFold, Boltz, etc.
"""
sequence = args.get("sequence") or ""
if not sequence:
return {"error": "predict_structure requires a 'sequence' argument"}
# TODO: replace this stub with your structure predictor.
return {
"pdb": ">dummy\nATOM ...",
"pLDDT": 0.0,
"pTM": 0.0,
"note": "stub implementation -- replace with your predictor",
}
def handle_design_binder(args: dict) -> dict:
"""Design a protein binder against a target. Real implementations
would call RFdiffusion followed by ProteinMPNN and AlphaFold2."""
return {"error": "design_binder not implemented in this stub"}
def handle_score_stability(args: dict) -> dict:
"""Score single-point stability. Real implementations might call
Rosetta, DDG_predictor, or a learned model."""
return {"error": "score_stability not implemented in this stub"}
TOOL_HANDLERS = {
"predict_structure": handle_predict_structure,
"design_binder": handle_design_binder,
"score_stability": handle_score_stability,
# ... add handlers for the other 14 tools here
}
# ---------------------------------------------------------------------------
# Dispatcher
# ---------------------------------------------------------------------------
@app.post("/")
def call_tool(
req: MCPRequest,
authorization: str | None = Header(default=None),
) -> dict:
if SHARED_TOKEN:
bearer = (authorization or "").removeprefix("Bearer ").strip()
if bearer != SHARED_TOKEN:
raise HTTPException(status_code=401, detail="Unauthorized")
handler = TOOL_HANDLERS.get(req.name)
if handler is None:
return {
"error": f"Unknown tool: {req.name}",
"available": sorted(TOOL_HANDLERS.keys()),
}
try:
return handler(req.arguments)
except Exception as e:
return {"error": f"{type(e).__name__}: {e}", "tool": req.name}
@app.get("/health")
def health() -> dict:
return {
"ok": True,
"implemented_tools": sorted(TOOL_HANDLERS.keys()),
"note": (
"This is the reference stub. Replace the handle_* functions "
"with your actual tool implementations before submitting to "
"the BioDesignBench leaderboard."
),
}
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