Analyzes code snippets by comparing them with best practices from official documentation found via web search. Identifies potential bugs, performance issues, and security vulnerabilities. Uses the configured Vertex AI model (${modelIdPlaceholder}) with Google Search. Requires
AI agents call code_analysis_with_docs to retrieve information from Vertex AI MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs static code analysis and documentation lookup. It reads code provided to it, queries external documentation via web search, and returns analysis results. No code execution occurs, no data is modified or deleted, and no external systems are altered. The tool is purely Read category as it gathers and presents information about potential issues without taking corrective action or triggering execution.
From the tool's definition Tool 'analyzes code snippets by comparing them with best practices' and 'identifies potential bugs, performance issues, and security vulnerabilities' — these are informational/analytical operations that retrieve and report findings without modifying code,…
Documented attack patterns abuse exactly the kind of access code_analysis_with_docs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Vertex AI MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for code_analysis_with_docs:
{
"version": "1",
"default": "deny",
"tools": {
"code_analysis_with_docs": {}
}
}code_analysis_with_docs is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Analyzes code snippets by comparing them with best practices from official documentation found via web search. Identifies potential bugs, performance issues, and security vulnerabilities. Uses the configured Vertex AI model (${modelIdPlaceholder}) with Google Search. Requires. It is categorised as a Read tool in the Vertex AI MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Vertex AI MCP Server MCP server in PolicyLayer and add a rule for code_analysis_with_docs: 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 Vertex AI MCP Server. Nothing to install.
code_analysis_with_docs 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 code_analysis_with_docs 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 code_analysis_with_docs. 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.
code_analysis_with_docs is provided by the Vertex AI MCP Server MCP server (shariqriazz/vertex-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 20 Vertex AI MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
20 Vertex AI MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.