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@qybbs/custom-bigquery-mcp

@qybbs/custom-bigquery-mcp

by qybbs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

execute_readonly_query

Run read-only SELECT queries against allowlisted BigQuery tables to inspect data safely without risking writes or unexpected costs.

Instructions

Execute a read-only BigQuery SQL query against allowed tables.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sql": "<sql>"
    },
    "name": "execute_readonly_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
sqlYesRead-only SELECT query

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does disclose two meaningful behavioral facts: execution is read-only and queries are restricted to allowed tables. It says nothing about cost, row/result limits, timeouts, or how non-allowed tables are rejected.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler; the read-only and allowed-table constraints appear immediately. Nothing is padded or redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations, so the description is the sole source of behavior. It covers the safety-relevant constraints but omits result handling, cost implications, and error behavior for disallowed queries, leaving gaps for a query-execution tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter, and schema coverage is 100%, so the schema already documents the sql field. The description adds marginal value by tying the parameter to the read-only/allowed-table constraint, but gives no syntax or dialect details. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Execute) plus resource (read-only BigQuery SQL query) and a scope constraint (allowed tables). It is clear what the tool does, though it never names or contrasts itself with the sibling tools such as estimate_query_cost or describe_table.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is given. With siblings like estimate_query_cost and describe_table present, the agent gets no hint about sequencing (e.g., estimate cost first, describe table to learn schema) or about when this tool is inappropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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