Low Risk

linear_search_issues

Searches Linear issues using flexible criteria. Supports filtering by any combination of: title/description text, team, status, assignee, labels, priority (1=urgent, 2=high, 3=normal, 4=low), and estimate. Returns up to 10 issues by default (configurable via limit).

How to control linear_search_issues ↓

What linear_search_issues does on Linear MCP Server

AI agents call linear_search_issues to retrieve information from Linear MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why linear_search_issues needs a policy

linear_search_issues retrieves and queries existing issue data based on specified criteria. It has no side effects, does not modify or delete data, and does not execute external operations. This is a straightforward Read operation with minimal risk if misused by an AI agent.

From the tool's definition The tool 'Searches Linear issues' and 'Returns up to 10 issues' with filtering capabilities. No mention of creating, modifying, deleting, or executing operations—purely a query/retrieval function.

Documented attack patterns abuse exactly the kind of access linear_search_issues gives an agent:

How to control linear_search_issues

PolicyLayer is an MCP gateway — it sits between your AI agents and Linear MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for linear_search_issues:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "linear_search_issues": {}
  }
}

linear_search_issues is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Linear MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about linear_search_issues

What does the linear_search_issues tool do? +

Searches Linear issues using flexible criteria. Supports filtering by any combination of: title/description text, team, status, assignee, labels, priority (1=urgent, 2=high, 3=normal, 4=low), and estimate. Returns up to 10 issues by default (configurable via limit). It is categorised as a Read tool in the Linear MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on linear_search_issues? +

Register the Linear MCP Server MCP server in PolicyLayer and add a rule for linear_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 MCP Server. Nothing to install.

What risk level is linear_search_issues? +

linear_search_issues is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit linear_search_issues? +

Yes. Add a rate_limit block to the linear_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.

How do I block linear_search_issues completely? +

Set action: deny in the PolicyLayer policy for linear_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.

What MCP server provides linear_search_issues? +

linear_search_issues is provided by the Linear MCP Server MCP server (jerhadf/linear-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Linear MCP Server tool call.

Start from Linear MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

5 Linear MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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