Content
# Google Ads MCP Server
This repo contains the source code for running an
[MCP](https://modelcontextprotocol.io) server that interacts with the
[Google Ads API](https://developers.google.com/google-ads/api).
## Tools
The server uses the
[Google Ads API](https://developers.google.com/google-ads/api/reference/rpc/latest/overview)
to provide several
[Tools](https://modelcontextprotocol.io/docs/concepts/tools) and [Resources](https://modelcontextprotocol.io/docs/concepts/tools) for use with LLMs and AI agents.
### Tools available
- `search`: Retrieves information about the Google Ads account.
- `get_resource_metadata`: Retrieves metadata about a Google Ads API resource type, for example "campaign". This is useful to understand the structure of the data and what fields are available for querying.
- `list_accessible_customers`: Returns ids of customers directly accessible
by the user authenticating the call.
### Configuring and Namespacing Tools
The Google Ads MCP server uses the `tools_config.yaml` to let you selectively enable or disable individual tools or tool categories (namespaces) and customize their namespace prefixes.
A default `tools_config.yaml` with all tools enabled is bundled with the package, so the server works out of the box with no extra setup. To customize your installation, the server resolves the configuration in the following order:
1. An explicit path set via the `GOOGLE_ADS_MCP_TOOLS_CONFIG` environment variable.
2. A `tools_config.yaml` file in the current working directory.
3. The default `tools_config.yaml` bundled with the package.
If an explicitly requested configuration file (via the environment variable) is missing, or any resolved file is invalid, the server raises an error and fails to start.
#### Configuration Example:
```yaml
namespaces:
# Option 1: Enable category 'customers' with default prefix -> "customers_list_accessible_customers"
customers: true
# Option 2: Enable category 'search' with a custom prefix -> "query_search"
search: "query"
# Option 3: Fine-grained control over tools in a category
metadata:
enabled: true
prefix: "metadata"
enabled_tools:
- get_resource_metadata: true
```
### Resources available
- `discovery-document`: Retrieve the Google Ads API discovery document. Provides the discovery document for the latest version of the Google Ads API, which describes the API surface, including resources, methods, and schemas. Host LLMs should access this resource to understand the structure of the Google Ads API and discover available features.
- `metrics`: Retrieve information about the metrics available for reporting in the Google Ads API.
- `segments`: Retrieve information about the segments available for reporting in the Google Ads API.
- `release-notes`: Retrieve the release notes for the latest version of the Google Ads API.
## Notes
1. The MCP Server will expose your data to the Agent or LLM that you connect to it.
1. If you have technical issues, please use the [GitHub issue tracker](https://github.com/googleads/google-ads-mcp/issues).
1. To help us collect usage data, you will notice an extra header has been added to your API calls: this data is used to improve the product.
## Setup instructions
Setup involves the following steps:
1. Configure Python.
1. Configure Developer Token.
1. Enable APIs in your project
1. Configure Credentials.
1. Configure your MCP client.
### Configure Python
[Install pipx](https://pipx.pypa.io/stable/#install-pipx).
### Configure Developer Token
Follow the instructions for [Obtaining a Developer Token](https://developers.google.com/google-ads/api/docs/get-started/dev-token).
Your developer token must have at least [Explorer access](https://developers.google.com/google-ads/api/docs/get-started/dev-token#access-levels) to query production accounts. New tokens may be automatically upgraded to Explorer access; if not, you can apply through the API Center. See the [access levels documentation](https://developers.google.com/google-ads/api/docs/get-started/dev-token#access-levels) for details.
If you see the error *"The developer token is only approved for use with test
accounts"*, your token does not yet have access to production accounts. See the
[access levels documentation](https://developers.google.com/google-ads/api/docs/access-levels)
for how to request the access level you need.
### Enable APIs in your project
[Follow the instructions](https://support.google.com/googleapi/answer/6158841)
to enable the following APIs in your Google Cloud project:
* [Google Ads API](https://console.cloud.google.com/apis/library/googleads.googleapis.com)
### Configure Credentials
#### Option 1: Using FastMCP OAuth Proxy
The server supports FastMCP's [OAuth proxy](https://gofastmcp.com/servers/auth/oauth-proxy) feature for dynamic user authentication. This is useful when running the server as a web service.
To enable it, set the following environment variables:
- `GOOGLE_ADS_MCP_OAUTH_CLIENT_ID`: Your Google Cloud OAuth 2.0 Client ID.
- `GOOGLE_ADS_MCP_OAUTH_CLIENT_SECRET`: Your Google Cloud OAuth 2.0 Client Secret.
- `GOOGLE_ADS_MCP_BASE_URL`: (Optional) The base URL where the server is accessible (defaults to `http://localhost:8080`).
Once this is enabled, you can authenticate to the API through your MCP client.
When these variables are set, the server automatically switches to the `streamable-http` transport (SSE/HTTP) instead of `stdio`.
You will need to run the server as a separate process and configure your MCP client to connect to the SSE endpoint (e.g., `http://localhost:8080/mcp`).
#### Option 2: Configure credentials using Application Default Credentials
Configure your [Application Default Credentials
(ADC)](https://cloud.google.com/docs/authentication/provide-credentials-adc).
Make sure the credentials are for a user with access to your Google Ads
accounts or properties.
Credentials must include the Google Ads API scope:
```
https://www.googleapis.com/auth/adwords
```
Check out
[Manage OAuth Clients](https://support.google.com/cloud/answer/15549257)
for how to create an OAuth client.
Here are some sample `gcloud` commands you might find useful:
- Set up ADC using user credentials and an OAuth desktop or web client after
downloading the client JSON to `YOUR_CLIENT_JSON_FILE`.
```shell
gcloud auth application-default login \
--scopes https://www.googleapis.com/auth/adwords,https://www.googleapis.com/auth/cloud-platform \
--client-id-file=YOUR_CLIENT_JSON_FILE
```
- Set up ADC using service account impersonation.
```shell
gcloud auth application-default login \
--impersonate-service-account=SERVICE_ACCOUNT_EMAIL \
--scopes=https://www.googleapis.com/auth/adwords,https://www.googleapis.com/auth/cloud-platform
```
When the `gcloud auth application-default` command completes, copy the
`PATH_TO_CREDENTIALS_JSON` file location printed to the console in the
following message. You will need this for a later step!
```
Credentials saved to file: [PATH_TO_CREDENTIALS_JSON]
```
#### Option 3: Configure credentials using the Google Ads API Python client library.
[Follow the instructions](https://developers.google.com/google-ads/api/docs/client-libs/python/)
to setup and configure the Google Ads API Python client library
If you have already done this and have a working `google-ads.yaml` , you can reuse this file!
In the utils.py file, change get_googleads_client() to use the load_from_storage() method.
### Configure your MCP client
Add the server to your MCP client's configuration. Below are examples for
popular clients.
#### Antigravity CLI / Antigravity Code Assist
1. Install [Antigravity CLI](https://antigravity.google/product/antigravity-cli) or Antigravity Code Assist.
1. Configure your server. Refer to the docs at [https://antigravity.google/docs/mcp](https://antigravity.google/docs/mcp) for details on setting up MCP servers.
- Option 1: Using FastMCP OAuth Proxy (Streamable HTTP)
You can run the server as a separate process and configure your MCP client to connect to the SSE endpoint (e.g., `http://localhost:8080/mcp`).
This also allows using FastMCP's [OAuth proxy](https://gofastmcp.com/servers/auth/oauth-proxy) feature for dynamic user authentication.
```json
{
"mcpServers": {
"google-ads-mcp": {
"httpUrl":"http://localhost:8080/mcp",
"env": {
"GOOGLE_PROJECT_ID": "YOUR_PROJECT_ID",
"GOOGLE_ADS_DEVELOPER_TOKEN": "YOUR_DEVELOPER_TOKEN"
}
}
}
}
```
- Option 2: the Application Default Credentials method
Replace `PATH_TO_CREDENTIALS_JSON` with the path you copied in the previous
step.
We also recommend that you add a `GOOGLE_CLOUD_PROJECT` attribute to the
`env` object. Replace `YOUR_PROJECT_ID` in the following example with the
[project ID](https://support.google.com/googleapi/answer/7014113) of your
Google Cloud project.
```json
{
"mcpServers": {
"google-ads-mcp": {
"command": "pipx",
"args": [
"run",
"--spec",
"git+https://github.com/googleads/google-ads-mcp.git",
"google-ads-mcp"
],
"env": {
"GOOGLE_APPLICATION_CREDENTIALS": "PATH_TO_CREDENTIALS_JSON",
"GOOGLE_PROJECT_ID": "YOUR_PROJECT_ID",
"GOOGLE_ADS_DEVELOPER_TOKEN": "YOUR_DEVELOPER_TOKEN"
}
}
}
}
```
- Option 3: the Python client library method
```json
{
"mcpServers": {
"google-ads-mcp": {
"command": "pipx",
"args": [
"run",
"--spec",
"git+https://github.com/googleads/google-ads-mcp.git",
"google-ads-mcp"
],
"env": {
"GOOGLE_PROJECT_ID": "YOUR_PROJECT_ID",
"GOOGLE_ADS_DEVELOPER_TOKEN": "YOUR_DEVELOPER_TOKEN"
}
}
}
}
```
#### Login Customer Id
If your access to the customer account is through a manager account, you will
need to add the customer ID of the manager account to the settings file.
See [here](https://developers.google.com/google-ads/api/docs/concepts/call-structure#cid) for details.
The final file will look like this:
```json
{
"mcpServers": {
"google-ads-mcp": {
"command": "pipx",
"args": [
"run",
"--spec",
"git+https://github.com/googleads/google-ads-mcp.git",
"google-ads-mcp"
],
"env": {
"GOOGLE_APPLICATION_CREDENTIALS": "PATH_TO_CREDENTIALS_JSON",
"GOOGLE_PROJECT_ID": "YOUR_PROJECT_ID",
"GOOGLE_ADS_DEVELOPER_TOKEN": "YOUR_DEVELOPER_TOKEN",
"GOOGLE_ADS_LOGIN_CUSTOMER_ID": "YOUR_MANAGER_CUSTOMER_ID"
}
}
}
}
```
#### Other MCP clients (Claude Code, Cursor, VS Code, etc.)
The `mcpServers` block format is the same across all MCP clients. Add the configuration shown above to the appropriate settings file for your client (e.g., `~/.claude/settings.json` for Claude Code, `.cursor/mcp.json` for Cursor, `.vscode/mcp.json` for VS Code with Copilot).
## Deployment to Google Cloud Platform
Instead of hosting this MCP server locally, you can host it on Google Cloud Run or on any other cloud-based infrastructure. This is useful if you want to share the server across different agents or run it as a web service.
Note that this only supports authentication with an OAuth Client ID and Client Secret pair through the OAuth proxy (Option #1 above).
### Prerequisites
1. A Google Cloud project.
2. The `gcloud` CLI installed, authenticated, and active project set.
```shell
gcloud config set project YOUR_PROJECT_ID
```
### Step 1: Build and Push Docker Image
You can use Cloud Build to build and push the image to Artifact Registry without needing Docker installed locally.
1. Create a repository in Artifact Registry:
```shell
gcloud artifacts repositories create mcp-servers --repository-format=docker --location=us-central1
```
2. Build and submit the image:
```shell
gcloud builds submit --tag us-central1-docker.pkg.dev/YOUR_PROJECT_ID/mcp-servers/google-ads-mcp:latest .
```
Replace `YOUR_PROJECT_ID` with your Google Cloud project ID.
### Step 2: Deploy to Google Cloud Run
Make sure to set the required environment variables:
- `GOOGLE_PROJECT_ID`: Your Google Cloud project ID.
- `GOOGLE_ADS_DEVELOPER_TOKEN`: The developer token you want the MCP server to use (see above).
- `GOOGLE_ADS_MCP_OAUTH_CLIENT_ID`: The OAuth Client ID you want the MCP server to use.
- `GOOGLE_ADS_MCP_OAUTH_CLIENT_SECRET`: The OAuth Client secret you want the MCP server to use.
- `GOOGLE_ADS_MCP_BASE_URL`: The base URL where your MCP server is accessible: this will be automatically assigned by Google Cloud Run after your first deployment. You can update the environment variables after deployment.
- `FASTMCP_HOST`: Set this to `0.0.0.0` to allow FastMCP to accept connections from all IP addresses.
```shell
gcloud run deploy google-ads-mcp \
--image us-central1-docker.pkg.dev/YOUR_PROJECT_ID/mcp-servers/google-ads-mcp:latest \
--platform managed \
--region us-central1 \
--allow-unauthenticated \
--set-env-vars="GOOGLE_PROJECT_ID=YOUR_PROJECT_ID,GOOGLE_ADS_DEVELOPER_TOKEN=YOUR_DEVELOPER_TOKEN,GOOGLE_ADS_MCP_OAUTH_CLIENT_ID=YOUR_CLIENT_ID,GOOGLE_ADS_MCP_OAUTH_CLIENT_SECRET=YOUR_CLIENT_SECRET,GOOGLE_ADS_MCP_BASE_URL=YOUR_BASE_URL,FASTMCP_HOST=0.0.0.0"
```
### Step 3: Configure MCP Client
Once deployed, update your MCP client configuration (refer to the docs at [https://antigravity.google/docs/mcp](https://antigravity.google/docs/mcp)) to use the Cloud Run URL.
```json
{
"mcpServers": {
"google-ads-mcp": {
"httpUrl": "https://your-cloud-run-url.a.run.app/mcp"
}
}
}
```
## Try it out
Launch your MCP client. You should see `google-ads-mcp` listed in the
available servers.
Here are some sample prompts to get you started:
- Ask what the server can do:
```
what can the ads-mcp server do?
```
- Ask about customers:
```
what customers do I have access to?
```
- Ask about campaigns
```
How many active campaigns do I have?
```
```
How is my campaign performance this week?
```
### Note about Customer ID
Your agent will need and ask for a customer id for most prompts. If you are
moving between multiple customers, including the customer ID in the prompt may
be simpler.
```
How many active campaigns do I have for customer id 1234567890
```
## Skills
This repository also provides [Agent Skills](https://agentskills.io/), which are specialized workflows and instructions that give AI agents specific expertise.
### Skills available
- `account-performance-diagnostics`: Diagnose account performance issues such as conversion loss, low lead flow, and lost opportunities. Located in `ads_mcp/skills/account-performance-diagnostics`.
### How to install skills
To use these skills, you need to point your skills-compatible AI agent to the skill directory.
For example, if you are using [Antigravity CLI](https://antigravity.google/product/antigravity-cli), you can install the skill by copying the folder to your skills directory or referencing it. See the [Antigravity CLI documentation](https://antigravity.google/docs/skills) for detailed instructions.
While that guide is specific to Antigravity CLI, Agent Skills are an open standard and can be loaded by any compatible agent or LLM tool that supports the format (e.g., Claude Code, Cursor).
## Contributing
Contributions welcome! See the [Contributing Guide](CONTRIBUTING.md).
