AI agents call get_todos to retrieve information from Kanban without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The 'get_' prefix is a standard convention for read operations that retrieve data without modification. The sibling tools on the same server include write and destructive operations, establishing context that this tool fits the retrieval pattern. No evidence suggests data modification, deletion, or execution of external operations.
From the tool's definition Tool name 'get_todos' indicates retrieval of todo items; no description provided, but naming convention and context among sibling tools (which include write/destructive operations like add_tag, delete_item, close_item) strongly suggests this is a read-only…
Documented attack patterns abuse exactly the kind of access get_todos gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Kanban, and nothing reaches the server without passing your rules. This is the rule we recommend for get_todos:
{
"version": "1",
"default": "deny",
"tools": {
"get_todos": {}
}
}get_todos is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_todos. It is categorised as a Read tool in the Kanban MCP Server, which means it retrieves data without modifying state.
Register the Kanban MCP server in PolicyLayer and add a rule for get_todos: 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 Kanban. Nothing to install.
get_todos 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_todos 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_todos. 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_todos is provided by the Kanban MCP server (multidimensionalcats/kanban-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Kanban, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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45 Kanban tools catalogued and risk-classified — across an index of 43,000+ MCP servers.