What is maestro-mcp GEMINI.md?

Instructions for using Maestro MCP from Gemini CLI. Maestro is a tool that checks and controls a group of computers and can assign work to AI agents.

Use them to check computer-fleet status, run commands on remote hosts, and start Maestro workflows from interactive or headless Gemini sessions.

They explain how to register the tool and use it inside a Gemini chat, avoiding the mistaken expectation that MCP tools are regular command-line commands.

How rmstxrx/maestro-mcp configures Gemini CLI

Reuse

Borrowing it

Nothing to install: this file belongs to rmstxrx/maestro-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/rmstxrx/maestro-mcp/main/GEMINI.md

Clone the repo

git clone --depth 1 https://github.com/rmstxrx/maestro-mcp

Made for: Gemini CLI.

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

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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.

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Per session 1,260 This file is loaded in full into every session.

When invoked 1,260 The same file — it is already loaded in full.

Security scan A 1 finding. 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	$0.01260	$0.01260
Opus 5.5	$0.00504	$0.00504
Sonnet 5.5	$0.00252	$0.00252
Haiku 4.5	$0.00126	$0.00126

Measured 2mo ago against content hash 8d91ce562122, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

maestro-mcp GEMINI.md scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

HTTP_CODE=\$(curl -s -o /tmp/result.json -w '%{http_code}' -H 'Authorization: Bearer \$RELAY_KEY' 'https://maestro.yourdomain.dev/tasks/TASK_ID/result')

GEMINI.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Maestro MCP — Gemini CLI Guide

Maestro integrates with Gemini CLI to provide fleet management and agent orchestration from within a Gemini chat session.

Setup

1. Register Maestro as an MCP server

gemini mcp add maestro \
  /path/to/maestro-mcp/.venv/bin/python \
  /path/to/maestro-mcp/server.py \
  --transport stdio

Verify it's registered:

gemini mcp list

Alternatively, the repo ships a .gemini/settings.json that registers Maestro automatically when Gemini CLI is run from the repo directory. Check the path inside it matches your local install.

2. Use Maestro tools from a session

MCP tools are not CLI subcommands — they are only accessible from within a Gemini chat session (interactive or headless). There is no gemini mcp call syntax.

Interactive session:

gemini
# Then in the session:
# > use maestro to check fleet status
# > run `nvidia-smi` on win-server via maestro

Headless (non-interactive):

gemini -p "Use maestro to check fleet status and report which hosts are down."

Core Fleet Workflows

All examples below are headless. The same prompts work interactively.

Check fleet status

gemini -p "Call the maestro status tool and summarise the result."

Execute a command on a host

gemini -p "Use maestro exec to run 'nvidia-smi' on host win-server and show the output."

Read a file (surgical)

gemini -p "Use maestro read to get the last 50 lines of /var/log/syslog on gpu-server."

Transfer a file

gemini -p "Use maestro transfer to upload ./src/main.py to ~/workspace/main.py on macbook."

Discover SSH hosts

gemini -p "Use maestro list_ssh_hosts to show available SSH hosts and which are already in the fleet."

Reconnect a host

gemini -p "Use maestro reconnect_host to reset the SSH connection to win-server."

Agent Orchestra

Maestro can dispatch Gemini CLI tasks as async background processes via the gemini tool. This is Gemini dispatching itself — useful for long-running agentic tasks you want to run in the background while the orchestrating session stays responsive.

Read the full file on GitHub · 170 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 · 170 lines · 1,260 tokens per session scan A 8d91ce562122

Subscribe to this mod's changes

maestro-mcp GEMINI.md is an instructions file published in the GitHub repository rmstxrx/maestro-mcp (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 1,260 tokens to every session, about $0.0050 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Building agents

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maestro-mcp: Instructions file for Gemini CLI