get_job_details
AI agents call get_job_details to retrieve information from LinkedIn MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves job posting details from LinkedIn via authenticated browser automation. It performs no modifications, deletions, or external operations — purely informational queries.
From the tool's definition Tool name 'get_job_details' and sibling tools like 'get_company_profile', 'get_person_profile', 'get_feed' all retrieve data without modifying it.
Attacks that exploit this kind of access
get_job_details. It is categorised as a Read tool in the LinkedIn MCP Server MCP Server, which means it retrieves data without modifying state.
Register the LinkedIn MCP Server MCP server in PolicyLayer and add a rule for get_job_details: 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 LinkedIn MCP Server. Nothing to install.
get_job_details 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_job_details 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_job_details. 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_job_details is provided by the LinkedIn MCP Server MCP server (stickerdaniel/linkedin-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.