gcp_firestore_run_query

Run a structured query on Firestore

SERVERGCP MCP Server SOURCEahmedselimmansor-ctrl/gcp_mcp_server

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/ahmedselimmansor-ctrl-gcp-mcp-server/gcp-firestore-run-query.md

WHAT IT DOES

What gcp_firestore_run_query does on GCP MCP Server

AI agents invoke gcp_firestore_run_query to trigger actions in GCP MCP Server. 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.

RISK

Why gcp_firestore_run_query is rated High

Running a structured query on Firestore is an Execute-category action. While queries are often read-only, 'structured query' in Firestore context can include operations that scan and return large amounts of data, and the tool may support queries that trigger side effects or expose sensitive data at scale.

From the tool's definition 'Run a structured query on Firestore' — the verb 'run' combined with 'structured query' indicates execution of a query operation against a live database

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs gcp_firestore_run_query safely

PolicyLayer is an MCP gateway: it sits between your AI agents and GCP MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For gcp_firestore_run_query, this is the rule to start with:

gcp_firestore_run_query Rate-limited

gcp_firestore_run_query stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "gcp_firestore_run_query": {
      "limits": [
        {
          "counter": "gcp_firestore_run_query_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GCP MCP Server, apply this rule, and every gcp_firestore_run_query call is checked against it from then on.

FAQ

Questions about gcp_firestore_run_query

What does the gcp_firestore_run_query tool do? +

Run a structured query on Firestore. It is categorised as a Execute tool in the GCP MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on gcp_firestore_run_query? +

Register the GCP MCP Server MCP server in PolicyLayer and add a rule for gcp_firestore_run_query: 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 GCP MCP Server. Nothing to install.

What risk level is gcp_firestore_run_query? +

gcp_firestore_run_query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit gcp_firestore_run_query? +

Yes. Add a rate_limit block to the gcp_firestore_run_query 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.

How do I block gcp_firestore_run_query completely? +

Set action: deny in the PolicyLayer policy for gcp_firestore_run_query. 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.

What MCP server provides gcp_firestore_run_query? +

gcp_firestore_run_query is provided by the GCP MCP Server MCP server (ahmedselimmansor-ctrl/gcp_mcp_server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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