get_about
AI agents call get_about to retrieve information from Nima Career without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool appears designed to retrieve biographical or 'about' information from a public career profile. No evidence suggests modification, deletion, execution, or financial operations. The server explicitly advertises pre-approved, read-only access to career material.
From the tool's definition Tool name 'get_about' and server purpose of exposing 'curated, public-safe career history' indicate data retrieval. Sibling tools like 'get_profile', 'get_project', 'get_role' all follow read-only patterns. Empty description limits certainty slightly.
Attacks that exploit this kind of access
get_about. It is categorised as a Read tool in the Nima Career MCP Server, which means it retrieves data without modifying state.
Register the Nima Career MCP server in PolicyLayer and add a rule for get_about: 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 Nima Career. Nothing to install.
get_about 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 get_about 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 get_about. 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.
get_about is provided by the Nima Career MCP server (nima-karami/nima-career-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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