CrawlForge MCP vs Google Ads MCP Server: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of CrawlForge MCP and Google Ads MCP Server — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
CrawlForge MCP
CrawlForge
MCP server giving AI agents 31 web scraping, search and extraction tools that return clean markdown or structured JSON.
Key features
- 31 MCP-Native Tools: Fetch, scrape, extract, search and research tools exposed through one MCP server that plugs into Claude, Cursor and LangChain.
- Clean Markdown and Structured JSON: Converts any URL into AI-ready markdown or schema-defined JSON in a single call.
- Site Mapping and Deep Crawling: map_site and crawl_deep discover and follow internal links across entire websites.
- Batch Scraping: Process hundreds of URLs in parallel with batch_scrape and retrieve paginated results.
- Browser Sessions and Actions: Keep a page alive across calls and scrape pages that need clicks, scrolls or form fills.
- Search and Research: search_web, reddit_search and deep research tools return ranked results and multi-source findings.
- Change Tracking: track_changes monitors pages with baselines, schedules and alerts.
- Credit-Based Metering: Each tool costs 1-5+ credits per call, so usage and cost stay transparent.
Best for
- Agent Web Access: Giving a coding or research agent live web data through one MCP server.
- RAG Ingestion: Converting documentation sites into clean markdown for retrieval pipelines.
- Competitor Monitoring: Tracking pricing or content changes on competitor pages with alerts.
- SEO Analysis: Checking where a domain ranks for keywords and generating llms.txt files.
- Lead and Market Research: Extracting structured data from product, directory and social pages at scale.
- Document Processing: Pulling text out of PDFs and other documents found online.
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.