This record as markdown: /tools/artemnikov-trello-mcp/assign-member.md
What assign_member does on Trello
AI agents use assign_member to create or update resources in Trello, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Trello environment.
Why assign_member is rated Medium
This tool creates or modifies a reversible assignment relationship between a board member and a card. It does not delete data, execute code, or move money. The impact is limited to updating card state, affecting only task assignments on a Trello board.
From the tool's definition Tool name 'assign_member' and description 'Assign a board member to a card' indicates modification of card metadata by adding a member assignment.
Attacks that exploit this kind of access
The rule that runs assign_member safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Trello, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For assign_member, this is the rule to start with:
assign_member stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Trello, apply this rule, and every assign_member call is checked against it from then on.
Questions about assign_member
Assign a board member to a card. It is categorised as a Write tool in the Trello MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Trello MCP server in PolicyLayer and add a rule for assign_member: 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 Trello. Nothing to install.
assign_member 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_member 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_member. 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_member is provided by the Trello MCP server (artemnikov/trello-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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