Google Ads MCP Server vs OzBrain: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Google Ads MCP Server and OzBrain — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Google Ads MCP Server
HireOtto
Hosted and open-source Model Context Protocol server to manage Google Ads from MCP clients (e.g., Claude) without Google Cloud or terminal setup.
Key features
- Hosted Remote MCP Server: A hosted endpoint that lets MCP clients (for example Claude Desktop) call Google Ads management tools without requiring Google Cloud setup, terminal use, or manual JSON edits.
- Self-Hosted Node.js/TypeScript Implementation: Open-source repositories provide Node.js and TypeScript servers you can run locally or in containers with simple .env-based configuration for Google Ads API credentials.
- Campaign Management Tools: Programmatic creation, retrieval, update, and budget adjustments for campaigns and ad groups, including parameters like campaign_id and budget_euros for direct modification.
- Unified MCP Tooling Endpoint: All tools are exposed via a consistent POST /api/mcp interface and support MCP streamable HTTP JSON-RPC (initialize, tools/list, tools/call) for agent interoperability.
- Analytics & Reporting: Export campaign and performance reports to CSV or JSON, request date-range filtered metrics, and retrieve conversion and cost statistics for optimization and reporting.
- Rate-Limit Handling & Retries: Built-in handling of Google Ads API rate limits with automatic retries to reduce manual error-handling and throttle issues.
- OAuth2 & Simple Configuration: Supports standard Google Ads OAuth2 credentials (client id/secret, refresh token, developer token) with inline JSON in .env for straightforward setup.
- Extensible Tools & Workflows: Modular tool implementations (accounts, campaigns, ads, keywords, conversions, performance, shopping) allowing customization and addition of new MCP tools.
- MCP-compatible toolset exposing Google Ads operations (campaigns, ad groups, ads, keywords, conversions, performance, analytics, shopping).
- POST /api/mcp endpoint with ToolResponse shape ({ok:true,data} | {ok:false,error}) and support for MCP Streamable HTTP JSON-RPC (initialize, tools/list, tools/call).
- Campaign management operations (create/update budgets, retrieve campaign stats).
- Analytics & reporting with export options to CSV or JSON (export_report with parameters: format, days).
- Autocomplete/keyword-sourcing tools (Google Autocomplete, Trends, keyword clustering in some forks).
- Configuration via .env (inline JSON or environment variables) and example .env templates included.
- OAuth2 support: instructions and scripts to obtain refresh tokens; requires Google Ads developer token, client ID/secret, refresh token, optional login-customer-id.
- Automatic handling of Google Ads API rate limits and retry logic.
- Multiple installation options: npm/pnpm (local/global), npx (no install), Docker images available on GHCR.
- Claude Desktop integration helpers and example claude_desktop_config.json for adding to MCP clients.
Best for
- Agent-driven Campaign Launches: Use an MCP-capable agent (like Claude) to create and configure Google Ads campaigns via natural-language prompts without touching Google Cloud or API JSON.
- Daily Campaign Monitoring and Alerts: Query campaign performance and get daily summaries or alerts from the MCP server for rapid status checks and anomaly detection.
- Automated Budget Optimization: Programmatically adjust daily budgets and bids across accounts using scheduled agent workflows or triggered rules exposed through MCP tools.
- Exporting Stakeholder Reports: Generate CSV or JSON exports of campaign, conversion, and cost metrics for sharing with teams or importing into BI tools.
- Keyword & Trend Research Integration: Combine Google Autocomplete, Trends, and Search Console-derived keyword data (available in some implementations) to inform campaign targeting from the same MCP endpoint.
- Local Development and Custom Extensions: Developers can run the open-source server locally, add custom tools (e.g., custom analytics or bidding strategies), and integrate with CI/CD or containerized deployments.
- Integrating Ads Management into ChatOps: Embed Google Ads operations into chat-based workflows or agent orchestrations so non-technical marketers can request changes conversationally.
- Manage Google Ads campaigns programmatically from an MCP-enabled chat assistant or desktop client (e.g., create/update campaigns, budgets).
- Run daily campaign monitoring and automated campaign optimization workflows via LLM agents.
- Export campaign reports for analysis (CSV/JSON) and feed results back into an agent for decision-making.
- Perform keyword research and clustering by combining Google Autocomplete/Trends data with Search Console (in supported forks).
- Integrate Google Ads controls into internal tooling without exposing direct Google Cloud or manual JSON configuration to non-technical users.
OzBrain
Monsef Holdings Pty Ltd
A hosted knowledge base every AI agent can read and write, shared across Claude, ChatGPT, Cursor and coding agents via connectors.
Key features
- Connector Setup: Add OzBrain from the connector menu in Claude or ChatGPT, sign in and approve - no code, SDK or installation required.
- Nested Article Retrieval: Knowledge is broken into nested pieces so an agent loads only the slice it needs, cutting tokens, latency and hallucination.
- Automatic Supersession: When newer thinking arrives, OzBrain revisits existing articles, marks the old as replaced and links forward to the current version.
- Staged Writes: Changes are proposed before they land, so multiple agents can write concurrently without clobbering one another.
- Change Ledger: Every edit records the agent, the article and the stated reason, giving a readable history of how the brain reached its current state.
- Shared Team Brains: Point a whole team's agents at one brain so context worked out in one person's chat is immediately available in everyone else's.
- Broad Client Support: Works with Claude, ChatGPT, Claude Code, Cursor, OpenClaw, Hermes Agent, Gemini Spark where available, and any connector-capable client.
- Markdown Export: Export everything as plain markdown at any time, including after cancellation, with deletion meaning the content is actually removed.
Best for
- Cross-Agent Continuity: Stop re-explaining the same project context when moving between Claude, ChatGPT and a coding agent.
- Single Source of Truth: Replace the scatter of launch-plan copies across Drive, Downloads, email and chat with one current version agents read from.
- Team Onboarding: Give a new teammate's agents the accumulated decisions, research and roadmap the rest of the team already has.
- Agent-Maintained Documentation: Let agents append findings and decisions as they work, with humans reviewing and correcting in the same place.
- Rules and Skills Storage: Keep coding standards, conventions and reusable skills where Claude Code and Cursor pick them up automatically.
- Long-Running Research: Accumulate customer research and competitive notes across many sessions instead of losing them to chat history.