# Directory Structure
```
├── .gitignore
├── img
│ └── inspector.png
├── LICENSE
├── package-lock.json
├── package.json
├── README.md
├── src
│ ├── cli.ts
│ └── index.ts
└── tsconfig.json
```
# Files
--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
```
node_modules/
build/
*.log
.env*
.DS_Store
```
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
```markdown
# amazon-ads-mcp-server
Connect to your Amazon Advertising Data by integrating your account with [MarketplaceAdPros](https://marketplaceadpros.com).
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:
```json
{
"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:
```json
{
"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`.
```json
{
"mcpServers": {
"marketplaceadpros": {
"type": "streamable-http",
"url": "https://app.marketplaceadpros.com/mcp"
}
}
}
```
Or, configure in [LibreChat](https://www.librechat.ai/) like:
```yaml
MAP:
type: streamable-http
url: https://app.marketplaceadpros.com/mcp
headers:
Authorization: "Bearer abcdefghijklmnop"
````
## Development
Install dependencies:
```bash
npm install
```
Build the server:
```bash
npm run build
```
For development with auto-rebuild:
```bash
npm run watch
```
### Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector), which is available as a package script:
```bash
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](https://modelcontextprotocol.io/introduction)
- [MarketplaceAdPros](https://marketplaceadpros.com?ref=github-amazon-ads-mcp-server) for enabling and sponsoring this project.
```
--------------------------------------------------------------------------------
/tsconfig.json:
--------------------------------------------------------------------------------
```json
{
"compilerOptions": {
"target": "ES2022",
"module": "Node16",
"moduleResolution": "Node16",
"outDir": "./build",
"rootDir": "./src",
"strict": true,
"esModuleInterop": true,
"skipLibCheck": true,
"forceConsistentCasingInFileNames": true
},
"include": ["src/**/*"],
"exclude": ["node_modules"]
}
```
--------------------------------------------------------------------------------
/src/cli.ts:
--------------------------------------------------------------------------------
```typescript
#!/usr/bin/env node
import { spawn } from 'child_process';
import { fileURLToPath } from 'url';
import { dirname, join } from 'path';
// Get the directory of the current module
const __filename = fileURLToPath(import.meta.url);
const __dirname = dirname(__filename);
// Path to the main index.js file
const serverPath = join(__dirname, 'index.js');
// Spawn the server process
const server = spawn('node', [serverPath], {
stdio: 'inherit',
env: process.env
});
// Handle process exit
server.on('exit', (code) => {
process.exit(code || 0);
});
// Handle signals to properly terminate the child process
process.on('SIGINT', () => {
server.kill('SIGINT');
});
process.on('SIGTERM', () => {
server.kill('SIGTERM');
});
```
--------------------------------------------------------------------------------
/package.json:
--------------------------------------------------------------------------------
```json
{
"name": "@marketplaceadpros/amazon-ads-mcp-server",
"version": "0.1.1",
"description": "A Model Context Protocol Server that runs as stdio, pointing to MarketplaceAdPros for Amazon Ads integration and MCP integration",
"type": "module",
"bin": {
"amazon-ads-mcp-server": "./build/cli.js"
},
"files": [
"build"
],
"scripts": {
"build": "tsc && node -e \"require('fs').chmodSync('build/index.js', '755'); require('fs').chmodSync('build/cli.js', '755')\"",
"prepare": "npm run build",
"watch": "tsc --watch",
"inspector": "npx @modelcontextprotocol/inspector build/index.js",
"clean": "rm -rf build",
"npm-publish": "npm run clean && npm run build && npm publish --access=public",
"start": "node build/cli.js"
},
"dependencies": {
"@modelcontextprotocol/sdk": "^1.11.0",
"dotenv": "^16.4.5"
},
"devDependencies": {
"@types/node": "^20.11.24",
"typescript": "^5.3.3"
},
"repository": {
"type": "git",
"url": "git+https://github.com/marketplaceadpros/amazon-ads-mcp-server.git"
},
"keywords": [
"claude",
"openai",
"mcp",
"model-context-protocol",
"ai",
"chat",
"llm"
],
"author": "MarketplaceAdPros",
"license": "MIT",
"engines": {
"node": ">=18"
}
}
```
--------------------------------------------------------------------------------
/src/index.ts:
--------------------------------------------------------------------------------
```typescript
#!/usr/bin/env node
import dotenv from "dotenv";
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
CallToolRequestSchema,
ListResourcesRequestSchema,
ListToolsRequestSchema,
ReadResourceRequestSchema,
ListPromptsRequestSchema,
GetPromptRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";
// Deps to run as a client
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
dotenv.config();
const URI = process.env.URI || 'https://app.marketplaceadpros.com/mcp';
const BEARER_TOKEN = process.env.BEARER_TOKEN;
const NAME = process.env.MCP_NAME || 'amazon-ads-mcp-server';
if (!URI) {
throw new Error("URI is required")
}
// console.log("starting...")
//
let transportOptions = {};
if (BEARER_TOKEN !== undefined) {
transportOptions = {
requestInit: {
headers: {
"Authorization": `Bearer ${BEARER_TOKEN}`
}
}
}
}
const transport = new StreamableHTTPClientTransport(
new URL(`${URI}`),
transportOptions
);
// console.log("making client...")
const client = new Client(
{
name: NAME,
version: "0.1.0"
}
);
// console.log("connecting to transport...")
await client.connect(transport);
const server = new Server(
{
name: NAME,
version: "0.1.0",
},
{
capabilities: {
tools: {},
},
}
);
/**
* Handler for listing resources.
*/
// server.setRequestHandler(ListResourcesRequestSchema, async () => {
// return await client.listResources();
// });
//
// /**
// * Handler for reading the contents of a specific resource.
// */
// server.setRequestHandler(ReadResourceRequestSchema, async (request) => {
// return await client.readResource({
// uri: request.params.uri,
// })
//
// });
/**
* Handler that lists available tools.
* Exposes a single "chat" tool that lets clients chat with another AI.
*/
server.setRequestHandler(ListToolsRequestSchema, async () => {
return await client.listTools();
});
/**
* Handler for the chat tool.
* Connects to an OpenAI SDK compatible AI Integration.
*/
server.setRequestHandler(CallToolRequestSchema, async (request) => {
return await client.callTool({
name: request.params.name,
arguments: request.params.arguments || {},
});
});
/**
* Handler that lists available prompts.
*/
// server.setRequestHandler(ListPromptsRequestSchema, async () => {
// return await client.listPrompts();
// });
//
// /**
// * Handler for the get prompt.
// */
// server.setRequestHandler(GetPromptRequestSchema, async (request) => {
// return await client.getPrompt({
// name: request.params.name,
// });
// });
/**
* Start the server using stdio transport.
* This allows the server to communicate via standard input/output streams.
*/
async function main() {
const transport = new StdioServerTransport();
await server.connect(transport);
}
main().catch((error) => {
console.error("Server error:", error);
process.exit(1);
});
```