Ahrefs Increases API and MCP Usage Limits by Up to 10x to Accelerate AI Agent Adoption

Ahrefs Increases API and MCP Connectivity Limits by Up to 10x

Ahrefs Pte. Ltd., the developer and provider of the all-in-one marketing tool 'Ahrefs', announced that as of April 28, it has significantly increased the usage limits for Ahrefs API and MCP connections across all paid plans: Lite, Standard, and Advanced.

In recent years, the use of generative AI tools like ChatGPT and Claude to directly access external data sources has expanded rapidly. Specifically, with the adoption of the Model Context Protocol (MCP), there is an increasing need to perform SEO, LLMO analysis, and competitive research directly within chat interfaces. In response, Ahrefs has decided to raise these limits to allow users to focus on analysis without worrying about usage restrictions. With this change, users can utilize up to 10 times the usage quota from major generative AI tools at no additional cost.

### Use Cases - **Real-time SEO analysis via AI agents**: Enables comparing backlink profiles of competitor sites by simply giving instructions in natural language. - **Automated report generation with no-code apps**: Automatically retrieves organic keywords and traffic data for custom dashboards and competitor monitoring apps. - **Advanced market research for data analysts**: Allows for the large-scale retrieval of search volume, keyword difficulty, and SERP feature occurrences for integration into custom analytical models. - **Automated PR/brand monitoring**: Builds systems where AI periodically checks brand radar and backlink data, notifying teams via Slack or email upon new mentions.

Takanori Kawarada, Ahrefs' Japan Marketing Lead, stated, 'The number of Ahrefs MCP users has doubled, showing that the demand for data analysis using AI agents is growing at a speed beyond our expectations. By providing an environment where users can access Ahrefs' big data more and deeper through AI, we will continue to support marketers and analysts in their strategic decision-making.'