amazon-ads-mcp-server▌
by marketplaceadpros
Fast, secure Amazon Ads MCP server for processing Amazon Marketing Cloud data and optimizing Amazon Advertising performa
amazon-ads-mcp-server
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Amazon sellers managing ad campaigns
- / PPC specialists analyzing advertising performance
- / E-commerce teams optimizing ad spend
capabilities
- / Access Amazon advertising campaigns and ad groups
- / Query advertising reports with natural language
- / Retrieve keywords and product ads data
- / Get MarketplaceAdPros recommendations and experiments
- / Analyze Sponsored Products, Brands, and Display campaigns
what it does
Connects to Amazon Advertising data through MarketplaceAdPros integration, providing access to campaigns, reports, and advertising resources. Query Amazon ads data and reports with plain English.
about
amazon-ads-mcp-server is a community-built MCP server published by marketplaceadpros that provides AI assistants with tools and capabilities via the Model Context Protocol. Fast, secure Amazon Ads MCP server for processing Amazon Marketing Cloud data and optimizing Amazon Advertising performa It is categorized under analytics data.
how to install
You can install amazon-ads-mcp-server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
amazon-ads-mcp-server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
amazon-ads-mcp-server
Connect to your Amazon Advertising Data by integrating your account with MarketplaceAdPros.
Provides access to:
- Advertising Resources in Sponsored Products, Sponsored Brands and Sponsored Display, like Campaigns, Ad Groups, Keywords, Product Ads, Targeting
- Reports and ability to query them with plain english.
- Marketplace Ad Pros Recommendations, Experiments and more with purchased subscription plan
Also available as a Streamable HTTP MCP Server by connecting to https://app.marketplaceadpros.com/mcp
Installation
To add the amazon-ads-mcp-server to your MCP client of choice, add the following to the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Env Vars
BEARER_TOKEN: The Bearer token you got from MarketplaceAdPros.com
Configuration
You can use it via npx in your Claude Desktop configuration like this:
{
"mcpServers": {
"marketplaceadpros": {
"command": "npx",
"args": [
"@marketplaceadpros/amazon-ads-mcp-server"
],
"env": {
"BEARER_TOKEN": "abcdefghijklmnop"
}
}
}
}
Or, if you clone the repo, you can build and use in your Claude Desktop configuration like this:
{
"mcpServers": {
"marketplaceadpros": {
"command": "node",
"args": [
"/path/to/amazon-ads-mcp-server/build/index.js"
],
"env": {
"BEARER_TOKEN": "abcdefghijklmnop"
}
}
}
}
Or, if your client supports the Streamable HTTP MCP Servers, you can just point to the MCP endpoint at https://app.marketplaceadpros.com/mcp.
{
"mcpServers": {
"marketplaceadpros": {
"type": "streamable-http",
"url": "https://app.marketplaceadpros.com/mcp"
}
}
}
Or, configure in LibreChat like:
MAP:
type: streamable-http
url: https://app.marketplaceadpros.com/mcp
headers:
Authorization: "Bearer abcdefghijklmnop"
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.
Acknowledgements
- Obviously the modelcontextprotocol and Anthropic teams for the MCP Specification. https://modelcontextprotocol.io/introduction
- MarketplaceAdPros for enabling and sponsoring this project.
FAQ
- What is the amazon-ads-mcp-server MCP server?
- amazon-ads-mcp-server is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for amazon-ads-mcp-server?
- This profile displays 62 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★62 reviews- ★★★★★Hiroshi Khan· Dec 24, 2024
amazon-ads-mcp-server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Sophia Sanchez· Dec 20, 2024
We wired amazon-ads-mcp-server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Kiara Brown· Dec 20, 2024
According to our notes, amazon-ads-mcp-server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Carlos Verma· Dec 20, 2024
amazon-ads-mcp-server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Isabella Lopez· Dec 16, 2024
I recommend amazon-ads-mcp-server for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Yuki Abbas· Nov 27, 2024
Useful MCP listing: amazon-ads-mcp-server is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Benjamin Brown· Nov 15, 2024
amazon-ads-mcp-server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Carlos Tandon· Nov 11, 2024
amazon-ads-mcp-server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★William Khanna· Nov 7, 2024
Strong directory entry: amazon-ads-mcp-server surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★William Brown· Oct 26, 2024
Useful MCP listing: amazon-ads-mcp-server is the kind of server we cite when onboarding engineers to host + tool permissions.
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