Get LinkedIn job details. Returns cleaned data in TOON format.
AI agents call get_job 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 publicly available LinkedIn job information and returns it in a formatted structure (TOON format). There are no indications of data modification, deletion, execution of commands, or financial transactions. It is a simple query operation that matches the 'Read' category for information retrieval tools with no side effects.
From the tool's definition Tool name 'get_job' and description 'Get LinkedIn job details' indicate data retrieval with no modification. The 'get_' prefix and all sibling tools (get_company, get_group, get_post, get_profile, etc.) are read-only retrieval operations.
Attacks that exploit this kind of access
Get LinkedIn job details. Returns cleaned data in TOON format. 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: 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 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 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. 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 is provided by the LinkedIn MCP Server MCP server (jing-yilin/linkedin-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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