Marvento Ads MCP

A fork of Google's official google-ads-mcp that adds write tools so an AI agent can build and run Google Ads campaigns, plus a one-command VPS deployment (Docker + Caddy, automatic HTTPS) so the server can be reached from any MCP client as a remote connector.

Upstream stays intact underneath: the OAuth login flow, GAQL search, get_resource_metadata and list_accessible_customers are Google's code. Everything below the line "Google Ads MCP Server" is the upstream README.

What this fork adds

Safety rails, enforced in code (ads_mcp/mutate.py):

• New campaigns are always created PAUSED. Enabling is a separate call.

• Anything that starts or raises spend, or removes something, needs confirm=true. Without it the call is validated by Google and returned as a preview; nothing changes.

• Daily budgets are capped by ADS_MCP_MAX_DAILY_BUDGET (server env, default 500).

• Every tool accepts validate_only=true for a dry run.

• Responsive search ad copy is checked against Google's limits before the API call.

Run the server read-only by setting the four write namespaces to false in tools_config.yaml.

Related MCP server: Ads MCP

Deploying

See deploy/: docker-compose.yml + Caddyfile for any Docker host, cloud-init.yaml + create_droplet.py for a fully automated DigitalOcean droplet. Operations, decisions and current state live in DOCUMENTATION.md and HANDOVER.md.

Google Ads API access is granted per Google Cloud project since 2026-09-09 (developer tokens are sunset). A new project starts at Test access; production accounts need Explorer or Basic. See DOCUMENTATION.md, section "Google access levels".

Google Ads MCP Server

This repo contains the source code for running an MCP server that interacts with the Google Ads API.

Tools

The server uses the Google Ads API to provide several Tools and Resources 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:

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.

2. If you have technical issues, please use the GitHub issue tracker.

3. 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.

2. Configure Developer Token.

3. Enable APIs in your project

4. Configure Credentials.

5. Configure your MCP client.

Configure Python

Install pipx.

After a version has been published to PyPI, you can run that exact version instead of following the latest repository state:

pipx run --spec "google-ads-mcp==X.Y.Z" google-ads-mcp

Configure Developer Token (Optional)

If your setup requires a developer token, follow the instructions for Obtaining a Developer Token.

Your developer token must have at least Explorer access 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 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 for how to request the access level you need.

Enable APIs in your project

Follow the instructions to enable the following APIs in your Google Cloud project:

• Google Ads API

Configure Credentials

Option 1: Using FastMCP OAuth Proxy

The server supports FastMCP's 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).

• GOOGLE_ADS_MCP_JWT_SIGNING_KEY: (Optional) Secret key used to sign FastMCP JWT tokens across multiple server instances or deployments.

• GOOGLE_ADS_MCP_STORAGE_TYPE: (Optional) Storage backend for OAuth state (filetree, redis, firestore, or memory).

• GOOGLE_ADS_MCP_STORAGE_PATH: (Optional) Directory path for filetree persistent storage.

• GOOGLE_ADS_MCP_STORAGE_REDIS_URL: (Optional) Redis URL for redis persistent storage.

• GOOGLE_ADS_MCP_STORAGE_FIRESTORE_PROJECT: (Optional) Google Cloud project for firestore persistent storage. Defaults to the project inferred from Application Default Credentials. Setting it selects the firestore backend even if GOOGLE_ADS_MCP_STORAGE_TYPE is unset.

• GOOGLE_ADS_MCP_STORAGE_FIRESTORE_DATABASE: (Optional) Firestore database name for firestore persistent storage. Defaults to (default).

• GOOGLE_ADS_MCP_STORAGE_ENCRYPTION_KEY: (Optional) Encryption key for stored OAuth tokens.

• GOOGLE_ADS_MCP_STORAGE_DISABLE_ENCRYPTION: (Optional) Set to true to disable token encryption.

The redis and firestore backends need their storage library installed alongside the server: pip install py-key-value-aio[redis] and pip install google-ads-mcp[firestore] respectively.

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 instead of stdio.

You will need to run the server as a separate process and configure your MCP client to connect to the Streamable HTTP endpoint (for example, http://localhost:8080/mcp).

Local WSL and Podman deployment

This deployment has been tested with rootless Podman in WSL and exposes a single Streamable HTTP endpoint at http://localhost:8080/mcp. Build the image from the repository inside WSL:

podman build --tag localhost/google-ads-mcp:latest --file Dockerfile .

Keep server credentials out of MCP client configuration. The tested Quadlet loads Google Ads and OAuth settings from a private host-side file through EnvironmentFile= and uses a separate named volume for persistent encrypted OAuth state:

[Container]
Image=localhost/google-ads-mcp:latest
PublishPort=127.0.0.1:8080:8080
EnvironmentFile=/absolute/host/path/google-ads-mcp.env
Volume=google-ads-mcp-oauth.volume:/var/lib/google-ads-mcp:rw
ReadOnly=true
NoNewPrivileges=true
DropCapability=all

The environment file and the OAuth-state volume serve different purposes: the volume does not contain the .env file. Keep the environment file outside the repository, restrict it to the service owner, and never commit it. Antigravity and Codex then need only the MCP endpoint and their own OAuth authorization; they do not need the server's Google Ads developer token, OAuth client secret, or signing and storage keys. Publish port 8080 only on the loopback interface when the server is intended for local agents.

The endpoint deliberately keeps stateful Streamable HTTP enabled. It supports legacy MCP 2025 clients that use Mcp-Session-Id and GET SSE as well as MCP 2026 clients that use sessionless POST requests and subscriptions/listen. Do not enable FastMCP's stateless_http option on this shared endpoint; doing so removes the legacy GET channel.

The server runs on FastMCP 4 (fastmcp>=4.0.3) paired with mcp[cli]==2.0.0. The Docker build also applies a version-guarded OAuth metadata workaround for Codex CLI 0.146. It stops advertising the RFC 9207 authorization-response iss parameter as mandatory while FastMCP still includes it in redirects. The build fails if the expected FastMCP version or patch location changes, so upgrades require explicit interoperability tests.

For Codex, configure and authenticate the server as described in the official Codex MCP documentation:

codex mcp add google_ads --url http://localhost:8080/mcp
codex mcp login google_ads

For Antigravity, configure the same URL as serverUrl in its MCP configuration. This key is required for Streamable HTTP in Antigravity 2.8.1 and Antigravity IDE 2.5.5; httpUrl is not accepted by those versions. After authentication, both clients should list these namespaced tools:

• customers_list_accessible_customers

• metadata_get_resource_metadata

• search_search

Option 2: Configure credentials using Application Default Credentials

Configure your Application Default 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 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.

  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.

  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 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 / Antigravity IDE

1. Install Antigravity or Antigravity IDE.

2. Configure your server. Refer to the docs at 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 Streamable HTTP endpoint (for example, http://localhost:8080/mcp). This also allows using FastMCP's OAuth proxy feature for dynamic user authentication.

  Antigravity 2.8.1 and Antigravity IDE 2.5.5 require serverUrl for a Streamable HTTP server. Do not use the older httpUrl key. Server-side credentials belong in the server process, not in this client configuration.

  {
    "mcpServers": {
      "google-ads-mcp": {
        "serverUrl": "http://localhost:8080/mcp"
      }
    }
  }

• Option 2: the Application Default Credentials method

  This remains a supported alternative, but it provides less credential isolation than the server-managed Streamable HTTP deployment above. The MCP client starts the server and its configuration contains the ADC file path and Google Ads developer token. Prefer the Quadlet deployment when several local clients share the same server or client configuration may be copied, synchronized, or inspected by other tools.

  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 of your Google Cloud project.

  {
    "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

  {
    "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 can either provide the manager account's customer ID per tool call via the optional login_customer_id parameter, or set GOOGLE_ADS_LOGIN_CUSTOMER_ID in the settings file as a default (the per-call login_customer_id parameter takes precedence when specified).

See here for details.

The final file will look like this:

{
  "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.

   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:

   gcloud artifacts repositories create mcp-servers --repository-format=docker --location=us-central1

2. Build and submit the image:

   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: (Optional) 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.

• GOOGLE_ADS_MCP_JWT_SIGNING_KEY: (Recommended for production) Persistent JWT signing key across Cloud Run instances.

• GOOGLE_ADS_MCP_STORAGE_TYPE: (Recommended for production) Storage backend to persist OAuth tokens across instances. Set it to firestore to use Firestore through Application Default Credentials, which needs no VPC connector, or to redis along with GOOGLE_ADS_MCP_STORAGE_REDIS_URL.

  Using firestore requires three things: build the image with the extra installed (change the Dockerfile to uv pip install --system .[firestore]), create a Firestore database in the project, since one is not provisioned automatically, and grant the Cloud Run service account roles/datastore.user. Note that entries are not expired automatically: the store filters expired entries on read but never deletes them, and expires_at is written as a string, so a Firestore TTL policy cannot collect them either. Plan on a periodic cleanup job for long-running deployments. Redis expires entries on its own.

• FASTMCP_HOST: Set this to 0.0.0.0 to allow FastMCP to accept connections from all IP addresses.

• GOOGLE_ADS_LOGIN_CUSTOMER_ID: Required if your access to the customer account is through a manager account. Set it to the customer ID of the manager account. See Login Customer Id above for details.

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,GOOGLE_ADS_MCP_JWT_SIGNING_KEY=YOUR_JWT_SIGNING_KEY,GOOGLE_ADS_MCP_STORAGE_TYPE=firestore,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) to use the Cloud Run URL.

{
  "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

Contributing

Changes to the read-only core belong upstream at googleads/google-ads-mcp (see its CONTRIBUTING.md). Changes to the write tools and the deployment kit go through this repository; AGENTS.md has the working rules.