- Install
- See source repository
- Transport
- http
- Auth
- API key
- Language
- TypeScript
- Tools exposed
- 4
- Official
- Community
The FetchSERP MCP server provides AI agents with access to search engine data and web intelligence tools. It serves as a bridge between the Model Context Protocol ecosystem and external SEO APIs, allowing agents to programmatically retrieve and analyze search results. This implementation is built in TypeScript as a community project.
Within the MCP architecture, FetchSERP specializes in search and web data retrieval capabilities. It would typically be used alongside other servers handling different domains. The server’s functionality is focused on SEO monitoring, keyword tracking, and web data extraction tasks.
Developers working on SEO automation or competitive intelligence tools would integrate this server. Agents can leverage it to monitor search rankings, benchmark performance, or gather web data without direct API integrations. The implementation requires access to the FetchSERP service’s API infrastructure.
Tools exposed
Resources
Requirements
- Node.js
- An API key for FetchSERP
- Internet access
Use cases
Pros & cons
Pros
- Focuses on search and SEO-specific functionality
- Likely integrates with commercial SERP APIs
- Well-suited for automated monitoring tasks
Cons
- Dependent on third-party search API credits
- Limited to search/SEO use cases
- Web scraping may be rate-limited
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FetchSERP