FetchSERP MCP Server

Overview

The FetchSERP MCP server bridges the gap between AI assistants and the rich data offered by the FetchSERP API. By exposing every endpoint of FetchSERP through the Model Context Protocol, it enables Claude and other AI clients to perform real‑time SEO research, SERP analysis, and web scraping without leaving the conversation. This is especially valuable for developers who need up‑to‑date search data and website metrics to inform content strategy, competitive intelligence, or technical SEO audits.

At its core, the server offers three main capabilities: SEO & Analysis, SERP & Search, and Web Scraping. The SEO module returns comprehensive domain information, backlink profiles, keyword search volumes, and AI‑powered page analyses. The SERP module fetches search results from multiple engines (Google, Bing, Yahoo, DuckDuckGo) and even renders JavaScript‑heavy pages to provide accurate snippet content. The web scraping layer supports both static page extraction and JavaScript execution, with optional country‑specific proxies to mimic local search contexts. Together these features give developers a single, consistent interface for gathering all the data they need to build smarter search‑centric applications.

The server is designed for flexibility. It can be run locally via , ensuring zero installation overhead and always the latest code, or deployed as a centralized HTTP service for teams that require shared credentials and scalable throughput. In both modes the FetchSERP API key is supplied through environment variables or HTTP headers, keeping authentication simple and secure. Developers can integrate the server into Claude Desktop, Claude’s API, or OpenAI’s API by adding a lightweight MCP configuration block, allowing AI agents to invoke complex search tasks with just a single tool call.

Real‑world use cases span content marketing, competitive analysis, and product research. For example, a marketing team can ask an AI assistant to “find the top 20 long‑tail keywords for ‘organic coffee beans’ in the US market” and receive a curated list with search volumes, domain authority scores, and SERP snippets—all in one response. An SEO specialist can trigger a “rank check” for a target keyword across multiple domains, or run an AI‑driven page audit that highlights on‑page issues and suggests optimizations. A data scientist might scrape a website’s entire sitemap, execute custom JavaScript to capture dynamic content, and then feed the data into a machine‑learning pipeline—all orchestrated through MCP.

What sets FetchSERP apart is its unified, AI‑friendly interface combined with the breadth of data it exposes. Unlike generic web‑scraping tools, it provides structured SEO metrics, domain authority scores, and search volume analytics out of the box. Unlike traditional APIs that require multiple calls and data stitching, FetchSERP’s MCP server delivers a single, coherent response tailored to the AI’s request. This integration reduces latency, simplifies codebases, and empowers developers to build smarter, data‑driven AI experiences with minimal friction.