Get detailed information about the next assignment to be performed by the requestor. Uses Get Next Work functionality to fetch the assignment most suitable for the current user.
AI agents call get_next_assignment to retrieve information from Pega DX 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 assignment data for the current user without any side effects. It is a simple query/read operation that returns information about work items. There is no capability to modify, execute, or delete anything. The low severity reflects minimal blast radius—misuse would only expose existing assignment information already accessible to the authenticated user.
From the tool's definition The tool description explicitly states it 'Get[s] detailed information about the next assignment' and 'fetch[es] the assignment', using only retrieval language with no modification, creation, deletion, or execution capabilities.
Documented attack patterns abuse exactly the kind of access get_next_assignment gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pega DX MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_next_assignment:
{
"version": "1",
"default": "deny",
"tools": {
"get_next_assignment": {}
}
}get_next_assignment is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get detailed information about the next assignment to be performed by the requestor. Uses Get Next Work functionality to fetch the assignment most suitable for the current user. It is categorised as a Read tool in the Pega DX MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Pega DX MCP Server MCP server in PolicyLayer and add a rule for get_next_assignment: 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 Pega DX MCP Server. Nothing to install.
get_next_assignment 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_next_assignment 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_next_assignment. 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_next_assignment is provided by the Pega DX MCP Server MCP server (marco-looy/pega-dx-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pega DX 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.
65 Pega DX MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.