bigquery_run_query

BigQuery SQL 쿼리 실행 (SELECT). GA4 analytics_* 테이블 분석에 사용.

SERVERMimi Seed SOURCE@yoonion/mimi-seed-mcp

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/yoonion-mimi-seed-mcp/bigquery-run-query.md

WHAT IT DOES

What bigquery_run_query does on Mimi Seed

AI agents invoke bigquery_run_query to trigger actions in Mimi Seed. 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 bigquery_run_query is rated High

BigQuery query execution is a classic Execute operation: it runs code (SQL) against an external service whose effects depend on the query arguments. Although the description hints at SELECT-only usage via '(SELECT)', the tool name and capability to 'run_query' indicate execution of arbitrary SQL statements.

From the tool's definition Tool name 'bigquery_run_query' combined with description stating it executes 'SQL 쿼리' (SQL queries) against BigQuery tables.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs bigquery_run_query safely

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

bigquery_run_query Rate-limited

bigquery_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": {
    "bigquery_run_query": {
      "limits": [
        {
          "counter": "bigquery_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 Mimi Seed, apply this rule, and every bigquery_run_query call is checked against it from then on.

FAQ

Questions about bigquery_run_query

What does the bigquery_run_query tool do? +

BigQuery SQL 쿼리 실행 (SELECT). GA4 analytics_* 테이블 분석에 사용. It is categorised as a Execute tool in the Mimi Seed MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on bigquery_run_query? +

Register the Mimi Seed MCP server in PolicyLayer and add a rule for bigquery_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 Mimi Seed. Nothing to install.

What risk level is bigquery_run_query? +

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

Can I rate-limit bigquery_run_query? +

Yes. Add a rate_limit block to the bigquery_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 bigquery_run_query completely? +

Set action: deny in the PolicyLayer policy for bigquery_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 bigquery_run_query? +

bigquery_run_query is provided by the Mimi Seed MCP server (@yoonion/mimi-seed-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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