AI agents call get_project_issues to retrieve information from Jira MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves existing issue data from a Jira project without modifying, creating, deleting, or executing any operations. It is a straightforward read operation analogous to a GET request, with minimal risk even if misused by an AI agent—it would only return data already accessible to the authenticated user.
From the tool's definition Tool name 'get_project_issues' and description 'Get all issues for a specific project' indicate a retrieval operation with no side effects.
Documented attack patterns abuse exactly the kind of access get_project_issues gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Jira MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_project_issues:
{
"version": "1",
"default": "deny",
"tools": {
"get_project_issues": {}
}
}get_project_issues is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get all issues for a specific project. It is categorised as a Read tool in the Jira MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Jira MCP Server MCP server in PolicyLayer and add a rule for get_project_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 Jira MCP Server. Nothing to install.
get_project_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 get_project_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 get_project_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.
get_project_issues is provided by the Jira MCP Server MCP server (sthirugn/jira-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Jira MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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11 Jira MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.