This record as markdown: /tools/1luvc0d3-metabase-mcp/update-dashboard.md
What update_dashboard does on Metabase MCP
AI agents use update_dashboard to create or update resources in Metabase MCP, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Metabase MCP environment.
Why update_dashboard is rated Medium
The tool modifies existing dashboard data (title, layout, cards, filters, etc.) but does not delete resources or execute arbitrary queries. Changes are reversible through subsequent updates.
From the tool's definition Tool name 'update_dashboard' and description 'Update an existing dashboard' indicate modification of dashboard configuration or content. This is a reversible change operation.
Attacks that exploit this kind of access
The rule that runs update_dashboard safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Metabase MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_dashboard, this is the rule to start with:
update_dashboard 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 Metabase MCP, apply this rule, and every update_dashboard call is checked against it from then on.
Questions about update_dashboard
Update an existing dashboard. It is categorised as a Write tool in the Metabase MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Metabase MCP server in PolicyLayer and add a rule for update_dashboard: 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 Metabase MCP. Nothing to install.
update_dashboard 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_dashboard 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_dashboard. 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_dashboard is provided by the Metabase MCP server (1luvc0d3/metabase-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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