AI agents invoke run_saved_view to trigger actions in Todos. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The tool executes a saved view, which could retrieve or process data based on stored parameters. While 'saved view' typically suggests read-only query execution (similar to a SQL view), the use of 'Execute' in the description and 'run' in the name suggests active invocation of logic rather than simple retrieval.
From the tool's definition Tool name contains 'run' and description states 'Execute a saved view' - indicates execution of a predefined query or operation.
Attacks that exploit this kind of access
Execute a saved view by slug or id. It is categorised as a Execute tool in the Todos MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Todos MCP server in PolicyLayer and add a rule for run_saved_view: 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 Todos. Nothing to install.
run_saved_view is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_saved_view 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 run_saved_view. 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.
run_saved_view is provided by the Todos MCP server (@hasna/todos). 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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