Analyzes data files and generates reports with visualizations
AI agents invoke analyze_data to trigger actions in MCP Server with Google ADK. 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.
Analyzing data files involves reading arbitrary files from the filesystem and executing analytical code/scripts to produce reports and visualizations. This goes beyond a simple read operation as it actively processes data, runs computations, and generates new artifacts.
From the tool's definition 'Analyzes data files and generates reports with visualizations' — processes data files and generates outputs, implying file I/O operations, code execution for analysis, and rendering of visualizations
Documented attack patterns abuse exactly the kind of access analyze_data gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Server with Google ADK, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_data:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_data": {
"limits": [
{
"counter": "analyze_data_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}analyze_data 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.
Free to start. No card required.
Analyzes data files and generates reports with visualizations. It is categorised as a Execute tool in the MCP Server with Google ADK MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP Server with Google ADK MCP server in PolicyLayer and add a rule for analyze_data: 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 MCP Server with Google ADK. Nothing to install.
analyze_data 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 analyze_data 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 analyze_data. 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.
analyze_data is provided by the MCP Server with Google ADK MCP server (zayedrais/ai_agent_with_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP Server with Google ADK, 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.
4 MCP Server with Google ADK tools catalogued and risk-classified — across an index of 43,000+ MCP servers.