Get issues assigned to the current user in a project
AI agents call get_assigned_issues to retrieve information from Jira-Context-MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a read operation that queries and retrieves data about assigned Jira tickets. It has no side effects, cannot modify or delete data, and poses minimal risk if misused by an AI agent—at worst it exposes information the authenticated user already has access to.
From the tool's definition Tool retrieves 'issues assigned to the current user in a project' with no modification capability mentioned. Sibling tools (get_issue, get_issue_types, get_issues_by_type, get_projects) are all read-only queries.
Documented attack patterns abuse exactly the kind of access get_assigned_issues gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Jira-Context-MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for get_assigned_issues:
{
"version": "1",
"default": "deny",
"tools": {
"get_assigned_issues": {}
}
}get_assigned_issues is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Get issues assigned to the current user in a project. It is categorised as a Read tool in the Jira-Context-MCP MCP Server, which means it retrieves data without modifying state.
Register the Jira-Context- MCP server in PolicyLayer and add a rule for get_assigned_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-Context-MCP. Nothing to install.
get_assigned_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_assigned_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_assigned_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_assigned_issues is provided by the Jira-Context- MCP server (rahulthedevil/jira-context-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Jira-Context-MCP, 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 Jira-Context-MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.