Predict the structure of a protein complex using AlphaFold2-Multimer.
AI agents invoke predict_complex to trigger actions in Protein Design. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool runs a computationally intensive external prediction algorithm (AlphaFold2-Multimer). It does not merely read stored data but actively executes a structure prediction pipeline. No data is permanently deleted or modified, and no financial transaction occurs, so Execute is the most appropriate category. Severity is medium due to the computational cost and potential for resource exhaustion if misused.
From the tool's definition 'Predict the structure of a protein complex using AlphaFold2-Multimer' — triggers an external computational prediction job via AlphaFold2-Multimer
Documented attack patterns abuse exactly the kind of access predict_complex gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Protein Design, and nothing reaches the server without passing your rules. This is the rule we recommend for predict_complex:
{
"version": "1",
"default": "deny",
"tools": {
"predict_complex": {
"limits": [
{
"counter": "predict_complex_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}predict_complex stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Predict the structure of a protein complex using AlphaFold2-Multimer. It is categorised as a Execute tool in the Protein Design MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Protein Design MCP server in PolicyLayer and add a rule for predict_complex: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Protein Design. Nothing to install.
predict_complex is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the predict_complex rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for predict_complex. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
predict_complex is provided by the Protein Design MCP server (jasonkim8652/protein-design-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Protein Design, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
19 Protein Design tools catalogued and risk-classified — across an index of 43,000+ MCP servers.