Unified tool for multimodal AI evaluation: set action=guide for reference thresholds/interpretation (CLIP, FID, VQA), or set action=clip_score / fid_score / vqa_accuracy / pipeline to compute real metrics via HuggingFace Inference API and VLM BYOK calls. One tool for both reference and computation.
Risk signalsHandles credentials or secrets (api_key) · High parameter count (16 properties)
Part of the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox server.
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AI agents use multimodal_eval_guide to create or modify resources in Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call multimodal_eval_guide repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"multimodal_eval_guide": {
"limits": [
{
"counter": "multimodal_eval_guide_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox policy for all 139 tools.
These attack patterns abuse exactly the kind of access multimodal_eval_guide gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Unified tool for multimodal AI evaluation: set action=guide for reference thresholds/interpretation (CLIP, FID, VQA), or set action=clip_score / fid_score / vqa_accuracy / pipeline to compute real metrics via HuggingFace Inference API and VLM BYOK calls. One tool for both reference and computation.. It is categorised as a Write tool in the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox MCP server in PolicyLayer and add a rule for multimodal_eval_guide: 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 Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox. Nothing to install.
multimodal_eval_guide is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the multimodal_eval_guide 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 multimodal_eval_guide. 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.
multimodal_eval_guide is provided by the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox MCP server (ia-qa/api). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 139 Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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