This record as markdown: /tools/com-googleapis-firestore-mcp/update-database.md
What update_database does on Mcp
AI agents use update_database to create or update resources in Mcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
database | object | Yes | Required. The database to update. |
updateMask | string | — | The list of fields to be updated. |
Parameters from the server's own tool schema.
Why update_database is rated Medium
An AI agent can call update_database faster than any human can review: one bad instruction and it creates or modifies resources in Mcp by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs update_database safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_database, this is the rule to start with:
update_database 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 Mcp, apply this rule, and every update_database call is checked against it from then on.
Questions about update_database
Update a Firestore database. It is categorised as a Write tool in the Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_database accepts 2 parameters: database, updateMask. Required: database. The full parameter table on this page comes from the server's own tool schema.
Register the MCP server in PolicyLayer and add a rule for update_database: 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 Mcp. Nothing to install.
update_database 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_database 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_database. 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_database is provided by the MCP server (https://firestore.googleapis.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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