What is google-ai-mcp AGENTS.md?

A developer guide for google-ai-mcp, an MCP server that connects coding agents to Google AI services such as Gemini, image and video generation, music, text-to-speech, and embeddings. It describes the project's entry points, architecture, ports, and common commands.

It is for onboarding, running the server and its web interface, checking code with tests and linting, running end-to-end tests, and creating a Claude Desktop bundle.

It helps developers understand where the main parts live and how to start, test, lint, and package the server without searching through the codebase first.

How sandraschi/google-ai-mcp configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to sandraschi/google-ai-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.

Copy the file

curl -O https://raw.githubusercontent.com/sandraschi/google-ai-mcp/master/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/sandraschi/google-ai-mcp

Made for: Codex, OpenCode.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/sandraschi/google-ai-mcp/agents-md/github.svg)](https://agentmods.dev/instructions/sandraschi/google-ai-mcp/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/sandraschi/google-ai-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/sandraschi/google-ai-mcp/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/sandraschi/google-ai-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/sandraschi/google-ai-mcp/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 781 This file is loaded in full into every session.

When invoked 781 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.

Model	Per session	Once invoked
Fable 5.1	$0.00781	$0.00781
Opus 5.5	$0.00312	$0.00312
Sonnet 5.5	$0.00156	$0.00156
Haiku 4.5	$0.00078	$0.00078

Measured 2mo ago against content hash e732ca135368, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

google-ai-mcp AGENTS.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 2mo 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.

AGENTS.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

google-ai-mcp — Agent Guide

FastMCP 3.2 MCP server for Google AI services — Gemini Chat, Nano Banana image gen, Veo video, Lyria music, Omni, one-shot TTS, embeddings, and LeWM world-model bridge.

Speech boundary: streaming Live/STT lives in speech-mcp; this repo keeps thin TTS only.

Entry Points

uv run google-ai-mcp → google_ai_mcp.server:main
.\start.ps1 — backend + frontend
just mcpb-pack — Claude Desktop .mcpb bundle

Quick Ref

uv run python -m google_ai_mcp.server
uv run pytest tests/ -q
just e2e
uv run ruff check src/ tests/

Ports

Service	Port
Backend (FastAPI + FastMCP HTTP)	11014
Frontend (Vite React)	11015

Architecture

src/google_ai_mcp/
  server.py            — FastMCP 3.2 server, MCP tools
  web.py               — FastAPI REST endpoints
  omni_client.py       — Gemini Omni multimodal
  chat_client.py       — Gemini/Gemma chat
  imagen_client.py     — Nano Banana image gen
  veo_client.py        — Veo 3.1 video gen
  lyria_client.py      — Lyria 3 music gen
  speech_client.py     — One-shot TTS (not Live)
  embeddings_client.py — Text embeddings
  clients_registry.py  — LRU-cached client factory
webapp/                — React MUI SPA (Vite)
native/                — Tauri 2.0 + PyInstaller sidecar
manifest.json          — MCPB Claude Desktop bundle

MCP Tools

Tool	Operations
`google_ai_chat`	chat, list_models
`google_ai_image`	generate, list_models
`google_ai_video`	generate, list_models
`google_ai_omni`	generate, list_models
`google_ai_music`	generate, list_models
`google_ai_speech`	tts, list_voices, list_models
`google_ai_embeddings`	embed, list_models
`google_ai_world`	health, train_prepare, infer_prepare
`google_ai_status`	Health check all services
`show_google_ai_status_card`	Prefab UI card

Standards

FastMCP 3.2+ portmanteau tool pattern — tools use operation enum param
Responses: structured dicts with success, message, domain-specific fields
Dual transport: stdio (Claude Desktop) + HTTP (MCP_TRANSPORT=http)
See mcp-central-docs for fleet-wide coding standards

Read the full file on GitHub · 89 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.

2mo ago First seen · 89 lines · 781 tokens per session scan A e732ca135368

Subscribe to this mod's changes

google-ai-mcp AGENTS.md is an instructions file published in the GitHub repository sandraschi/google-ai-mcp (2 stars, last pushed 9d ago), licensed MIT. It adds 781 tokens to every session, about $0.0031 per session on Opus 5.5. 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.

docker fastmcp gemini gemini-omni generative-ai google-ai

google-ai-mcp AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
google-ai-mcp AGENTS.mdsandraschi/google-ai-mcp	Instructions file	2	9d ago	MIT	A	781	Codex, OpenCode
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next.js AGENTS.mdvercel/next.js	Instructions file	143k	yesterday	MIT	A	7,461	Codex, OpenCode
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vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
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google-ai-mcp: Instructions file for Codex