AI agents invoke ld_pruning to trigger actions in Gwas. 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.
The tool performs a computational operation (LD pruning) that filters/removes variants from a dataset to produce a reduced independent set. While 'removes' suggests data modification, this is a standard bioinformatics processing step that typically writes a new filtered output rather than irreversibly deleting source data.
From the tool's definition 'Prune SNPs based on linkage disequilibrium (LD). Removes variants in high LD to create an independent set.'
Attacks that exploit this kind of access
Prune SNPs based on linkage disequilibrium (LD). Removes variants in high LD to create an independent set. It is categorised as a Execute tool in the Gwas MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Gwas MCP server in PolicyLayer and add a rule for ld_pruning: 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 Gwas. Nothing to install.
ld_pruning 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 ld_pruning 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 ld_pruning. 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.
ld_pruning is provided by the Gwas MCP server (muslus/gwas-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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