AI agents call search_issues to retrieve information from Linear without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The search_issues tool retrieves and queries issue data based on filter criteria. It performs no side effects, creates no new data, executes no external commands, and does not delete or modify resources. This is a standard read operation typical of search functionality.
From the tool's definition Tool name 'search_issues' and description 'Search for issues with advanced filtering options' indicate a search/query operation with no modification or deletion of data.
Attacks that exploit this kind of access
Search for issues with advanced filtering options. It is categorised as a Read tool in the Linear MCP Server, which means it retrieves data without modifying state.
Register the Linear MCP server in PolicyLayer and add a rule for search_issues: 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 Linear. Nothing to install.
search_issues 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 search_issues 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 search_issues. 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.
search_issues is provided by the Linear MCP server (mkusaka/mcp-server-linear). 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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