Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/pvoo/bigquery-mcp/claude-mdgit clone --depth 1 https://github.com/pvoo/bigquery-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/pvoo/bigquery-mcp/claude-md)<a href="https://agentmods.dev/instructions/pvoo/bigquery-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/pvoo/bigquery-mcp/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01465 | $0.01465 |
| Opus 5 | $0.00732 | $0.00732 |
| Sonnet 5 | $0.00293 | $0.00293 |
| Haiku 4.5 | $0.00146 | $0.00146 |
Grade A, and why
bigquery-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
BigQuery MCP server - A Python implementation using FastMCP to provide BigQuery operations through the Model Context Protocol. The project is optimized for navigating large datasets efficiently while keeping LLM context minimal.
Development Commands
# Setup (recommended approach)
make install # Setup environment and pre-commit hooks
# OR manual setup:
uv sync # Install all dependencies
uv run pre-commit install # Setup git hooks
# Run the server
make run # Runs bigquery-mcp console script
# OR:
uv run bigquery-mcp --project YOUR_PROJECT --location US
# Development workflow
make check # Run all quality checks (lint, type, format)
make test # Run pytest test suite
make inspect # Launch MCP inspector for testing
# Individual tools
uv run ruff check . # Lint code
uv run ruff format . # Format code
uv run mypy # Type checking (configured for src/ directory)
uv run pytest # Run tests
# Build and distribution
make build # Build wheel file
make clean # Clean build artifacts
Architecture
Modular Package Structure
- src/bigquery_mcp/server.py: Main entry point and CLI argument handling
- src/bigquery_mcp/bigquery_tools.py: Core MCP tool implementations
- src/bigquery_mcp/auth.py: Authentication helpers and error formatting
- src/bigquery_mcp/query_safety.py: SQL query validation and safety checks
- FastMCP decorators for clean tool definitions
- Async operations for BigQuery interactions
Tool Implementation Pattern
@mcp.tool()
async def tool_name(param: str) -> dict:
"""Tool description for MCP."""
# Input validation with helpful error messages
# BigQuery operation with proper client handling
# Comprehensive error handling with context
# Return structured response optimized for LLM consumption
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 150 lines · 1,465 tokens per session scan A bd2cd98af1d4
bigquery-mcp CLAUDE.md is an instructions file published in the GitHub repository pvoo/bigquery-mcp (9 stars, last pushed 3mo ago), licensed MIT. It adds 1,465 tokens to every session, about $0.0073 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
MCP-MySQL-Ops copilot-instructions.md
Instructions for call518/MCP-MySQL-Ops, covering mcp mysql operations server - ai coding agent instructions, architecture overview, core components, key patterns and correct - mysql returns uppercase column names.
statelessagent AGENTS.md
AGENTS.md instructions for sgx-labs/statelessagent, covering same — operational guide for agents, build & test, required: cgo is needed for sqlite3 + sqlite-vec, build and test (all packages, race detector, verbose).
bigquery-mcp CLAUDE.md
Instructions for aicayzer/bigquery-mcp, covering claude development guidelines, task management, working with tasks.md, version management and code style.
TechWordTranslatorMCP-Server CLAUDE.md
Claude Code instructions for josego85/TechWordTranslatorMCP-Server, covering claude.md — techwordtranslator mcp server, project overview, architecture, layered structure and key design decisions.
RivalSearchMCP AGENTS.md
AGENTS.md instructions for damionrashford/RivalSearchMCP, covering agents.md, project overview, development commands, setup & running and install dependencies.
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