update_workflow
Update a workflow definition and its steps (full replacement of steps if provided).
This record as markdown: /tools/todo-for-ai-todo-for-ai-mcp/update-workflow.md
What update_workflow does on Todo for AI MCP Server
AI agents use update_workflow to create or update resources in Todo for AI MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Todo for AI MCP Server environment.
Why update_workflow is rated Medium
An AI agent can call update_workflow faster than any human can review: one bad instruction and it creates or modifies resources in Todo for AI MCP Server by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs update_workflow safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Todo for AI MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_workflow, this is the rule to start with:
update_workflow 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 Todo for AI MCP Server, apply this rule, and every update_workflow call is checked against it from then on.
Questions about update_workflow
Update a workflow definition and its steps (full replacement of steps if provided). It is categorised as a Write tool in the Todo for AI MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Todo for AI MCP Server MCP server in PolicyLayer and add a rule for update_workflow: 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 Todo for AI MCP Server. Nothing to install.
update_workflow 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 update_workflow 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 update_workflow. 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.
update_workflow is provided by the Todo for AI MCP Server MCP server (todo-for-ai/todo-for-ai-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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