mcp-walmart-ads
MCP server for Walmart Connect Ads APIs, enabling AI agents to execute any Sponsored Search or Display API endpoint with automatic RSA-SHA256 signing and download display snapshots.
README
Walmart Connect Advertising APIs
<!-- mcp-name: io.github.alyiox/mcp-walmart-ads -->
MCP server for Walmart Connect Ads APIs — Sponsored Search and Display.
Exposes two tools — a generic API proxy (walmart_ads_api) and a display-snapshot downloader (walmart_ads_download_display_snapshot). The AI agent decides which endpoint to call; the server handles RSA-SHA256 signing and auth headers automatically.
Features
- One tool, any endpoint — no code changes needed when APIs evolve
- Supports both Sponsored Search and Display API families
- Multi-region, multi-environment (production + staging) via config file
- Per-request RSA-SHA256 signing with automatic header construction
- Large responses truncated with full data available via MCP resource URI
- Bundled API reference docs served as MCP resources so the agent knows endpoint schemas
Requirements
- Python 3.13+
- Walmart Connect Partner Network credentials (consumer ID, RSA key pair, bearer token)
Quick start
Set up your config (see Configuration), then run the server:
# Run directly with uvx (no clone needed)
npx -y @modelcontextprotocol/inspector uvx mcp-walmart-ads
# Or run from source
git clone https://github.com/alyiox/mcp-walmart-ads.git
cd mcp-walmart-ads
uv sync
npx -y @modelcontextprotocol/inspector uv run mcp-walmart-ads
Configuration
The config file lives under your home directory at ~/.config/mcp-walmart-ads/config.json.
Windows note:
~maps to%USERPROFILE%(typicallyC:\Users\<you>), so the full path is%USERPROFILE%\.config\mcp-walmart-ads\config.json.
1. Create the config directory and copy the example
# Unix-like (macOS, Linux, WSL, …)
mkdir -p ~/.config/mcp-walmart-ads/keys/us
cp config.example.json ~/.config/mcp-walmart-ads/config.json
# Windows (PowerShell)
New-Item -ItemType Directory -Force "$env:USERPROFILE\.config\mcp-walmart-ads\keys\us"
Copy-Item config.example.json "$env:USERPROFILE\.config\mcp-walmart-ads\config.json"
2. Edit ~/.config/mcp-walmart-ads/config.json
{
"response_cache_ttl": 3600,
"truncate_threshold": 51200,
"regions": {
"US": {
"production": {
"consumer_id": "your-consumer-id",
"private_key": "./keys/us/prod.pem",
"private_key_version": "1",
"bearer_token": "your-bearer-token",
"base_urls": {
"search": "https://developer.api.walmart.com/api-proxy/service/WPA/Api/v1",
"display": "https://developer.api.walmart.com/api-proxy/service/display/api/v1"
}
},
"staging": {
"consumer_id": "your-staging-consumer-id",
"private_key": "./keys/us/staging.pem",
"private_key_version": "1",
"bearer_token": "your-staging-bearer-token",
"base_urls": {
"search": "https://developer.api.stg.walmart.com/api-proxy/service/WPA/Api/v1",
"display": "https://developer.api.us.stg.walmart.com/api-proxy/service/display/api/v1"
}
}
}
}
}
3. Place your RSA private key PEM files in ~/.config/mcp-walmart-ads/keys/
Key paths in the config are resolved relative to the config directory, so ./keys/us/prod.pem resolves to ~/.config/mcp-walmart-ads/keys/us/prod.pem.
| Config field | Description |
|---|---|
response_cache_ttl |
Seconds to keep truncated responses in memory (default 3600) |
truncate_threshold |
Response byte limit before truncation (default 51200) |
regions.<R>.<E>.consumer_id |
Your Walmart Connect consumer ID |
regions.<R>.<E>.private_key |
Path to RSA private key PEM (relative to config dir or absolute) |
regions.<R>.<E>.private_key_version |
Key version string (default "1") |
regions.<R>.<E>.bearer_token |
OAuth bearer token |
regions.<R>.<E>.base_urls.search |
Sponsored Search API base URL |
regions.<R>.<E>.base_urls.display |
Display API base URL |
Tools
walmart_ads_api
Execute any Walmart Connect Ads API endpoint. The agent picks the method and path; the server handles RSA-SHA256 signing.
| Parameter | Required | Description |
|---|---|---|
region |
yes | e.g. US |
env |
yes | production or staging |
ad_type |
yes | search or display |
method |
yes | GET, POST, PUT, or DELETE |
path |
yes | e.g. /api/v1/campaigns |
params |
no | Query string parameters (JSON object) |
body |
no | JSON request body for POST/PUT (object or array) |
walmart_ads_download_display_snapshot
Download a display snapshot file (report or entity). Display snapshot URLs require authenticated requests, so this tool handles the signing automatically. Use it with the snapshot ID from the details field after polling a display snapshot to done status.
| Parameter | Required | Description |
|---|---|---|
region |
yes | e.g. US |
env |
yes | production or staging |
snapshot_id |
yes | Snapshot ID from the details URL |
advertiser_id |
yes | Advertiser ID used when creating the snapshot |
MCP resources
API reference docs
The server bundles API reference docs as MCP resources so the agent can read endpoint schemas on demand. One resource per endpoint group, following the URI pattern wmc://docs/{ad_type}/{group} — for example wmc://docs/search/campaigns or wmc://docs/display/audiences.
The full list is generated from the markdown files in src/mcp_walmart_ads/docs/. Current groups:
| Search | Display |
|---|---|
| campaigns | campaigns |
| ad-groups | ad-groups |
| ad-items | targeting |
| keywords | audiences |
| placements | itemsets |
| bid-multipliers | itemset-campaign-association |
| sponsored-brands | catalog |
| sponsored-videos | forecast |
| catalog-item-search | creative |
| snapshot-reports | creative-associations |
| top-search-trends | video |
| advanced-insights | folder |
| stats | snapshot-reports |
| audit-snapshot | stats |
| brand-landing-page |
Dynamic resources
| Resource URI | Description |
|---|---|
wmc://config |
Available regions, environments, and ad types from your config |
wmc://responses/{request_id} |
Full body of a truncated API response (cached in memory, TTL from config) |
wmc://curl/{request_id} |
Reproducible cURL command for a previous API request |
MCP host examples
Cursor
Add to .cursor/mcp.json:
{
"mcpServers": {
"walmart-ads": {
"command": "uvx",
"args": ["mcp-walmart-ads"]
}
}
}
Claude Code
Add to your Claude Code MCP config:
{
"mcpServers": {
"walmart-ads": {
"command": "uvx",
"args": ["mcp-walmart-ads"]
}
}
}
Codex
[mcp_servers.walmart-ads]
command = "uvx"
args = ["mcp-walmart-ads"]
OpenCode
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"walmart-ads": {
"type": "local",
"enabled": true,
"command": ["uvx", "mcp-walmart-ads"]
}
}
}
GitHub Copilot
{
"inputs": [],
"servers": {
"walmart-ads": {
"type": "stdio",
"command": "uvx",
"args": ["mcp-walmart-ads"]
}
}
}
Development
uv sync --group dev # install deps
uv run pytest # run tests
uv run ruff check . # lint
uv run ruff format . # format
uv run pyright # type check
Contributing
Open issues or PRs. Follow existing style and add tests where appropriate.
License
MIT. See LICENSE.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.