Google Open-Sources an MCP Server for the Google Ads API, Bringing LLM-Native Access to Ads Data

Google has open-sourced a Model Context Protocol (MCP) server that provides read-only access to the Google Ads API for agentic and LLM applications. storehouse googleads/google-ads-mcp An MCP server implementation in Python offers two tools today: search (GAQL questions on advertising accounts) and list_accessible_customers (Calculation of customer resources). This includes setup through pipxGoogle Ads developer token, OAuth2 scope (https://www.googleapis.com/auth/adwords), and Gemini CLI/Code Assist integration through a standard MCP client configuration. The project is labeled “experimental”.

So, why does it matter?

MCP is emerging as a common interface for wiring models in external systems. By sending a context server to the Ads API, Google reduces integration costs for LLM agents who need campaign telemetry, budget pacing, and performance diagnostics without any special SDK glue.

how it works? (developer view)

• Etiquette: MCP standardizes the “tools” that models can implement with typed parameters and responses. Ad MCP servers serve advertising tools mapped to Google Ads API operations; MCP clients (Gemini CLI/Code Assist, others) discover and call them during a session.
• Authenticity and Scope: You enable the Google Ads API in the cloud project, obtain a developer token, and configure the application default credentials or the Ads Python client. The required scope is adwordsFor the manager-account hierarchy, set a login customer ID.
• Client Wiring: Add a ~/.gemini/settings.json Entry pointing to MCP server invocation (pipx run git+https://github.com/googleads/google-ads-mcp.git google-ads-mcp) and pass credentials through env vars. then query through /mcp In Gemini or by indicating for campaigns, demonstrations etc.

ecosystem signal

Google’s server comes amid widespread MCP adoption across vendors and open-source clients, solidifying MCP as a practical path to agent-to-SaaS interoperability. For PPC and development teams experimenting with agentive workflows, Reference Server is a low-friction way to perform LLM-assisted QA, anomaly triage, and validating weekly reporting without granting write privileges.

key takeaways

• google open source a read only Google Ads API mcp serverDisplaying two devices: search (GAQL) and list_accessible_customers,
• Implementation details: Python project on GitHub (googleads/google-ads-mcp, apache-2.0 license, marked experimentalinstall/run via pipx and configure OAuth2 with https://www.googleapis.com/auth/adwords Scope (Dev Token + Optional Login-Customer ID).
• works with MCP-Compatible Client (for example, Gemini CLI/Code Assist) so that agents can issue GAQL queries and analyze ad accounts via natural-language prompts.

conclusion

In practice, Google’s open-source Google Ads API MCP Server Provides teams with a standards-based, read-only path for LLM agents to run GAQL queries against ad accounts without any specific SDK wiring. Apache-licensed repo marked experimental, exposes search And list_accessible_customersAnd integrates with MCP clients like Gemini CLI/Code Assist; Production access must be for the OAuth scope (adwords), developer token management, and the data-exposure warning noted in the README.

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Michael Sutter is a data science professional and holds a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michael excels in transforming complex datasets into actionable insights.