Borrowing it
Nothing to install: this file belongs to JoaoCarabetta/basedosdados-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/JoaoCarabetta/basedosdados-mcp/main/GEMINI.mdgit clone --depth 1 https://github.com/JoaoCarabetta/basedosdados-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/joaocarabetta/basedosdados-mcp/gemini-md)<a href="https://agentmods.dev/instructions/joaocarabetta/basedosdados-mcp/gemini-md"><img src="https://agentmods.dev/badge/instructions/joaocarabetta/basedosdados-mcp/gemini-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 5.1 | $0.01055 | $0.01055 |
| Opus 5 | $0.00528 | $0.00528 |
| Sonnet 5 | $0.00211 | $0.00211 |
| Haiku 4.5 | $0.00105 | $0.00105 |
Grade A, and why
basedosdados-mcp GEMINI.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 7d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEMINI.md
This file provides guidance to Gemini when working with code in this repository.
Project Overview
This is a Model Context Protocol (MCP) server for Base dos Dados, Brazil's open data platform. The server provides AI-optimized tools and resources for accessing datasets, tables, columns, and generating SQL queries through the MCP protocol.
Architecture
The project follows a modular structure to separate concerns and improve maintainability.
src/basedosdados_mcp/main.py: Main application entry point for the MCP server.src/basedosdados_mcp/server.py: Initializes the core MCP server instance.src/basedosdados_mcp/config.py: Stores configuration, like the GraphQL API endpoint.src/basedosdados_mcp/models.py: Contains Pydantic data models for API objects.src/basedosdados_mcp/utils.py: Includes helper functions for data processing and search ranking.src/basedosdados_mcp/graphql_client.py: Manages communication with the Base dos Dados GraphQL API.src/basedosdados_mcp/resources.py: Defines and handles MCP resources (e.g., help text).src/basedosdados_mcp/tools.py: Implements the core MCP tools exposed to the client.pyproject.toml: Project configuration, dependencies, and entry points.README.md: High-level project documentation.
Key Components
Modular MCP Server (src/basedosdados_mcp/)
- GraphQL Client: Connects to the Base dos Dados API (
https://backend.basedosdados.org/graphql). - AI-Optimized Tools: Designed for single-call, comprehensive data retrieval with ready-to-use BigQuery references.
- Smart Search: Features Portuguese accent normalization, acronym prioritization, and intelligent result ranking.
- Enhanced Resources: Provides context-aware help and guidance formatted for LLM consumption.
AI-Optimized Tools
search_datasets: Performs an enhanced search with table/column counts and BigQuery references. It includes Portuguese accent normalization (populacao→população), prioritizes common acronyms (RAIS, IBGE), and provides a comprehensive structure preview.get_dataset_overview: Returns a complete dataset view in a single call, including all tables, column counts, and full BigQuery references (e.g.,basedosdados.br_ibge_populacao.municipio).get_table_details: Provides comprehensive table information, including all columns with their types and descriptions, plus multiple sample SQL queries for analysis.explore_data: Enables multi-level data exploration with different modes (overview,detailed) for either a quick summary or a deep dive into the data structure.
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.
- 7d ago First seen · 86 lines · 1,055 tokens per session scan A c128113421fe
basedosdados-mcp GEMINI.md is an instructions file published in the GitHub repository JoaoCarabetta/basedosdados-mcp (1 stars, last pushed 1y ago), licensed MIT. It adds 1,055 tokens to every session, about $0.0053 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.
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