More by Sachin Pitch your Startup, App or Hardware or post a Startup Event or Startup Job
Company profile:
Startup name: Easy Fetcher
Tagline: Easy Fetcher makes it easier to collect data from websites without spending hours copying information manually or building complicated scraping tools. Use it for SEO research, lead generation, competitor research, market research, and other workflows where you need data from the web. It’s built for marketers, founders, agencies, researchers, and anyone who needs web data without wanting to deal with the technical side of scraping.
Elevator Pitch: Easy Fetcher turns websites into usable data in a few clicks. No coding, no complicated scraping setup, and no hours spent copying information manually.
Built for marketers, SEO professionals, researchers, agencies, and founders, Easy Fetcher makes it easy to collect the web data you need and put it to work faster.
Target Market: Marketers, SEO professionals, agencies, sales teams, researchers, startups, and businesses that need to collect data from websites.
How will you make money?: Easy Fetcher follows a subscription-based SaaS model. Users can choose a monthly or annual plan based on how much data they need to collect, with higher plans offering more usage and additional features.
We also plan to serve agencies and larger teams that need higher data volumes, multiple users, and more advanced workflows through higher-tier and custom plans.
How much capital have you raised?: None
Website: https://www.easyfetcher.com/
City/Country: INDIA
AI-assisted summary:
Easy Fetcher is a marketing analytics platform that combines conventional SEO reporting with AI-search visibility tracking and AI-assistant integrations. It is aimed at agencies, brands, SEO professionals, freelancers, and solo marketers that want to monitor how their sites perform in Google search and AI answer engines from one product. (Source: https://www.easyfetcher.com/)
Problem and target users
SEO operators increasingly need to work across Google Search Console, Google Analytics 4, keyword-ranking tools, client reports, and emerging AI-search surfaces, creating a fragmented workflow for diagnosing performance and communicating results. Easy Fetcher positions itself as a single workspace for SEO, GEO, and AEO performance, with particular emphasis on agencies and professionals managing multiple client domains. (Source: https://www.easyfetcher.com/)
The company’s plans signal a clear segmentation strategy: Starter is positioned for solo marketers and indie makers, Pro for freelancers with multiple clients, and Business for agencies operating at greater scale. (Source: https://www.easyfetcher.com/pricing)
Its AI-assistant angle is based on the Model Context Protocol, an open protocol designed to connect AI applications with external data sources and tools. (Source: https://modelcontextprotocol.io/specification/2024-11-05/index)
Product and solution
Easy Fetcher connects Google Search Console and GA4 data, then presents search, traffic, and engagement information alongside rank tracking, prompt tracking, AI visibility monitoring, backlink tracking, and client reporting. (Source: https://www.easyfetcher.com/)
- Search and analytics reporting: The platform says users can examine Search Console and GA4 data by dimensions including country, page, query, and device, while placing impressions, sessions, clicks, and related measures in a unified workflow. (Source: https://www.easyfetcher.com/)
- Keyword and prompt monitoring: It offers Google keyword-rank monitoring and tracks selected customer prompts across ChatGPT, Gemini, Claude, Perplexity, and Google AI experiences. (Source: https://www.easyfetcher.com/)
- AI traffic and visibility: Easy Fetcher says it can group traffic from ChatGPT, Copilot, and Perplexity using a customer’s own GA4 data, and identify where AI answers cite a brand. (Source: https://www.easyfetcher.com/features)
- AI-native data access: Through its MCP connection, the company says users can ask for Search Console, GA4, and PageSpeed data in plain English from supported AI clients, including Claude, ChatGPT, and Perplexity. (Source: https://www.easyfetcher.com/)
- Client delivery: The product includes white-label dashboards and client-ready reporting, reflecting its focus on service providers that need to turn performance data into deliverables rather than spreadsheets. (Source: https://www.easyfetcher.com/pricing)
On data handling, Easy Fetcher states that it stores OAuth credentials needed to access connected Google accounts but does not copy, store, or cache customers’ underlying marketing and analytics data; it says the data is fetched in real time and sent to the AI client. These are company policy statements rather than independently audited security claims. (Source: https://www.easyfetcher.com/privacy)
Business model, pricing signals, and traction
Easy Fetcher uses a subscription SaaS model with annual-billing prices of $14 per month for Starter, $69 per month for Pro, and $124 per month for Business. (Source: https://www.easyfetcher.com/pricing)
Plans differ primarily by included domains and monthly AI credits: Starter includes one domain and 100 credits, Pro includes five domains and 200 credits, and Business includes 10 domains and 300 credits. (Source: https://www.easyfetcher.com/pricing)
The company’s public pricing page includes a 30-day money-back guarantee and states that subscriptions can be cancelled at any time. (Source: https://www.easyfetcher.com/pricing)
Easy Fetcher’s public website includes customer testimonials, but the reviewed materials do not provide independently verifiable funding, customer-count, revenue, or usage figures, so its commercial traction cannot be assessed from public evidence alone. (Source: https://www.easyfetcher.com/)
Expert take
Easy Fetcher’s strongest positioning is not merely AI-search tracking; it is the combination of first-party SEO data, agency-oriented reporting, and conversational access to that data through MCP. That could be compelling for operators who already trust their Search Console and GA4 properties but want less manual analysis.
The key open questions are reliability of AI-visibility measurement, breadth of supported data sources, and whether the product can sustain differentiation as established SEO platforms add similar AI-search features. Its MCP-based design also makes permissioning and data governance central product concerns, since MCP integrations expose external data and tool capabilities that require informed user consent and appropriate access controls. (Source: https://modelcontextprotocol.io/specification/2024-11-05/index)
Note: Information is based on publicly available sources at the time of writing and summarized by AI.
Pitch your Startup, App or Hardware or post a Startup Event or Startup Job