mcp-geo: Instructions file for Gemini CLI

GEMINI.md

mcp-geo GEMINI.md is an instructions file for Gemini CLI from chris-page-gov/mcp-geo. It costs 846 tokens per session, scanned A, original, MIT.

Project instructions for the mcp-geo server, a service that gives AI assistants access to United Kingdom geographic and statistical data. It documents the project's technologies, folders, architecture, and ways to run it.

In plain words
What is it for?
Use it when working on address lookups, boundary analysis, demographic data, map rendering, MCP connections, or the project's Python, Svelte, Docker, and database code.
Why use it?
It gives coding agents the context needed to make changes that fit the existing server, data sources, database, frontend, and development setup.

Instructions file for Gemini CLI

Written for Gemini CLI: the file is GEMINI.md. Also seen: mentions Gemini CLI.

This is chris-page-gov/mcp-geo's own configuration. It tells Gemini CLI how to work on mcp-geo itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp-geo configures →

Reuse

Borrowing it

Nothing to install: this file belongs to chris-page-gov/mcp-geo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/chris-page-gov/mcp-geo/main/GEMINI.md
Clone the repo
git clone --depth 1 https://github.com/chris-page-gov/mcp-geo

Made for: Gemini CLI.

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Per session 846 This file is loaded in full into every session.
When invoked 846 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00846 $0.00846
Opus 5 $0.00423 $0.00423
Sonnet 5 $0.00169 $0.00169
Haiku 4.5 $0.00085 $0.00085

Measured 10d ago against content hash d36bb40f904f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

mcp-geo 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 10d 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.

GEMINI.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEMINI.md - MCP Geo Server Context

This document provides essential context and instructions for AI agents (like Gemini) interacting with the MCP Geo Server repository.

Project Overview

MCP Geo Server is a research-oriented Model Context Protocol (MCP) server designed to provide AI assistants with access to UK geospatial data (via Ordnance Survey) and statistical data (via Office of National Statistics and NOMIS). It enables tools for address lookups, administrative boundary analysis, demographic statistics, and map rendering.

Main Technologies

  • Language: Python 3.11+
  • Framework: FastAPI / Uvicorn (HTTP transport)
  • Protocol: Model Context Protocol (MCP) - supports both STDIO and HTTP transports.
  • Data Sources: Ordnance Survey (OS) APIs, ONS Open Geography, NOMIS.
  • Database: PostGIS / pgRouting (for boundary and routing features).
  • Frontend: Svelte + Vite (for the playground UI).
  • DevOps: Docker, Devcontainers, GitHub Actions.

Architecture

  • server/: Core FastAPI application, routers, and MCP transport logic.
    • server/mcp/: MCP-specific implementations (tools, resources, http transport).
    • server/stdio_adapter.py: JSON-RPC 2.0 adapter for STDIO communication.
  • tools/: Individual Python modules implementing specific domain tools (e.g., os_places, ons_data, admin_lookup).
  • playground/: Svelte-based interactive UI for testing tools and exploring resources.
  • scripts/: Utility scripts for running the server, trace proxies, and maintenance tasks.
  • docs/: Extensive documentation covering specifications, research, and usage.

Building and Running

Prerequisites

  • Python 3.11+
  • OS_API_KEY (required for OS tools)
  • Docker (optional, but recommended for PostGIS features)

Development Setup

# Install dependencies with test and dev extras
pip install -e .[test,dev]

# Set up environment variables
cp .env.example .env
# Edit .env and add your OS_API_KEY

Running the Server

  • HTTP Transport (Default):
    python run.py
    # or
    uvicorn server.main:app --reload
    
    The server will be available at http://localhost:8000.

Read the full file on GitHub · 88 lines

Changes

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.

  1. 10d ago First seen · 88 lines · 846 tokens per session scan A d36bb40f904f

Subscribe to this mod's changes

mcp-geo GEMINI.md is an instructions file published in the GitHub repository chris-page-gov/mcp-geo (3 stars, last pushed 1mo ago), licensed MIT. It adds 846 tokens to every session, about $0.0042 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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