Predict binding affinity for a protein complex using Boltz.
AI agents call predict_affinity_boltz to retrieve information from Protein Design without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool runs a computational prediction to estimate binding affinity. It queries/analyzes input data and returns a result (affinity score), with no side effects on external systems, databases, or files. It is analogous to a read or fetch operation in the context of computational biology tools.
From the tool's definition 'Predict binding affinity for a protein complex using Boltz' — 'predict' indicates a read/query operation that computes and returns information without modifying data.
Documented attack patterns abuse exactly the kind of access predict_affinity_boltz 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_affinity_boltz:
{
"version": "1",
"default": "deny",
"tools": {
"predict_affinity_boltz": {}
}
}predict_affinity_boltz is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Predict binding affinity for a protein complex using Boltz. It is categorised as a Read tool in the Protein Design MCP Server, which means it retrieves data without modifying state.
Register the Protein Design MCP server in PolicyLayer and add a rule for predict_affinity_boltz: 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_affinity_boltz is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the predict_affinity_boltz 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_affinity_boltz. 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_affinity_boltz 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.