assign_work
AI agents use assign_work to create or update resources in Claude Team MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Claude Team MCP environment.
The tool appears to modify work assignments within a multi-agent coordination system. Without a description, classification relies on naming patterns and context. 'Assign' implies creating or updating task state (Write category), affecting which agent works on what.
From the tool's definition Tool name 'assign_work' combined with sibling tools like 'assign_fix', 'auto_assign', and 'add_task' suggests modification of task assignments or work allocation state.
Attacks that exploit this kind of access
assign_work. It is categorised as a Write tool in the Claude Team MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Claude Team MCP server in PolicyLayer and add a rule for assign_work: 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 Claude Team MCP. Nothing to install.
assign_work is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the assign_work 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 assign_work. 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.
assign_work is provided by the Claude Team MCP server (lakshan12367/mcp). 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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