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amazon_ads_mcp AGENTS.md

amazon_ads_mcp AGENTS.md is an instructions file for Codex, OpenCode from KuudoAI/amazon_ads_mcp. It costs 7,786 tokens per session, scanned A, original, MIT.

A set of project instructions for developing Amazon Ads MCP, a Python server that connects AI assistants to Amazon's advertising services through the Model Context Protocol (MCP).

In plain words
What is it for?
Use it when installing, running, checking, or contributing to the Amazon Ads MCP project. It covers Python and uv setup, Docker startup, Claude connection, linting, and tests.
Why use it?
It gives coding agents and developers a required setup and validation process, reducing missed dependencies, linting problems, and failed tests.

Instructions file for CodexOpenCode

not rated 67 1mo ago A scan 7,786 tokens original MIT
View the source file KuudoAI/amazon_ads_mcp kuudo.com
Install

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.

agentmods
npx agentmods add instructions/kuudoai/amazon_ads_mcp/agents-md
Clone the repo
git clone --depth 1 https://github.com/KuudoAI/amazon_ads_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.

agentmods badge for amazon_ads_mcp AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/kuudoai/amazon_ads_mcp/agents-md.svg)](https://agentmods.dev/instructions/kuudoai/amazon_ads_mcp/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/kuudoai/amazon_ads_mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/kuudoai/amazon_ads_mcp/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 7,786 This file is loaded in full into every session.
When invoked 7,786 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
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 $0.07786 $0.07786
Opus 5 $0.03893 $0.03893
Sonnet 5 $0.01557 $0.01557
Haiku 4.5 $0.00779 $0.00779

Measured 5d ago against content hash 24b1203dc6b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

amazon_ads_mcp AGENTS.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 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.

Makes network callslowCapability

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

4. **Download via HTTP**: Open URL in browser or use curl
AGENTS.md · 871 lines

How it starts

The opening of the file, as written. The whole thing — 871 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Amazon Ads MCP Development Guidelines

Audience: LLM-driven engineering agents and human developers

Amazon Ads MCP is a Python framework (Python ≥3.10) for integrating Amazon Advertising API with Model Context Protocol (MCP) servers. This project provides a complete toolkit for building AI-powered advertising applications with comprehensive campaign management, reporting, and optimization capabilities.

Do This First (for Agents)

  • Ensure Python ≥3.10 and uv are installed
  • uv sync to install dependencies
  • Start the server: docker compose up -d
  • Connect Claude to the MCP server (HTTP):
    • claude mcp add amazon-ads-mcp -- python -m amazon_ads_mcp.server --transport http --port 9080
  • Verify: claude mcp list and use /mcp inside Claude

Required Development Workflow

CRITICAL: Always run these commands in sequence before committing:

# Install dependencies
uv sync                              # Install dependencies

# Validate code
uv run ruff check --fix             # Lint and auto-fix
uv run pytest                        # Run full test suite

All must pass - tests/linting must be clean before committing.

Agent Ops (LLM Guidance)

  • Preambles: Send a brief 1–2 sentence note before running tool commands.
  • Plans: Use TodoWrite for multi-step work; keep exactly one in_progress step.
  • Edits: Use Edit or MultiEdit to modify files; keep changes focused and avoid unrelated edits.
  • Testing: Run the smallest relevant tests first; do not fix unrelated failures.
  • Sandboxing: Assume workspace-write FS and restricted network; prefer local resources over external APIs unless keys are present.

Agent Success Playbook

Follow these steps for reliable outcomes in Claude contexts:

  1. Understand & Plan
  • Clarify task type: API integration, MCP connectivity, Docker, tests, or GitHub workflow.
  • Post a short preamble and, for multi-step work, create a minimal TodoWrite with exactly one in_progress step.
  1. Connect & Verify (MCP + Server)
  • Start server: docker compose up -d (Amazon Ads MCP at http://localhost:9080).
  • Add MCP to Claude (HTTP):
    • claude mcp add amazon-ads-mcp -- python -m amazon_ads_mcp.server --transport http --port 9080
  • Verify in Claude: claude mcp list then /mcp → run a tool (e.g., list profiles).

Read the full file on GitHub · 871 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. 5d ago First seen · 871 lines · 7,786 tokens per session scan A 24b1203dc6b7

Subscribe to this mod's changes

amazon_ads_mcp AGENTS.md is an instructions file published in the GitHub repository KuudoAI/amazon_ads_mcp (67 stars, last pushed 1mo ago), licensed MIT. It adds 7,786 tokens to every session, about $0.0389 per session on Opus 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 2026-08-30.

Marketing and SEOamazonamazon-adsamazon-ads-apiamazon-ads-mcpamazon-advertisingamazon-advertising-api
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