Supercharge your AI with Grepsr. Automate complex web scraping and reporting with AI.
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
Grepsr lets you take full control of your web scraping data directly through your AI client. Instead of logging into a dashboard to check on crawls or download reports, you tell your agent exactly what data you need—whether it's the latest product price list or an entire competitor report history—and get structured records right in your workflow.
What your AI can do
Create webhook
Sets up a new webhook URL to notify your systems when a specific report is updated.
Get me
Gets basic details about your current Grepsr account configuration.
Get latest data
Retrieves the most recent scraped dataset for a given report ID.
Retrieve current usage statistics and API rate limit information for your Grepsr account.
See an overview of all scraping projects you have set up in the platform.
Fetch a complete list of all active reports and crawlers configured for your account.
Manually start an immediate crawl run for any specific report to refresh your data.
Query and get the actual, clean dataset from a specified report or historical run.
Review the full log of runs for a particular report to audit data quality and status.
Ask an AI about this
Compatible AI Apps
OAuth 2.0 CompatibleWaiting for input…
Grepsr: 12 Tools for Data Extraction
These tools let your agent manage every aspect of your web scraping workflow, from listing projects to retrieving the final structured record.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Grepsr on VinkiusCreate Webhook
Sets up a new webhook URL to notify your systems when a specific report is updated.
Get Me
Gets basic details about your current Grepsr account configuration.
Get Latest Data
Retrieves the most recent scraped dataset for a given report ID.
Get Report Data
Queries and fetches structured records from a specific, named report.
Get Report Details
Retrieves the metadata and setup configuration for any specified report.
Get Report History
Pulls a log of all previous execution runs (histories) for a given report.
Get Usage Stats
Checks your account's API usage and current request rate limits.
List Integrations
Lists all active data delivery connections, like S3 or SFTP.
List Projects
Shows a list of every scraping project you have created.
List Reports
Lists all web scraping reports and crawlers within your account.
List Webhooks
Shows a list of the webhook URLs currently set up for a specific report.
Run Report
Manually starts an on-demand crawl run to refresh data for any specified report.
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Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
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Make Your AI Do More
Start with Grepsr, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Grepsr. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 12 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Tracking web data usually involves jumping between dashboards and API calls.
Today, if your team needs updated competitor pricing, someone has to log into the scraping dashboard. They check the run status, then they might have to click a button to manually trigger an update. After that, they often download a massive CSV file and copy-paste key fields into a spreadsheet for analysis.
With this MCP, you just prompt your agent: 'Refresh the competitor pricing report.' The agent handles triggering the crawl, monitors its status using 'get_report_history', waits for success, and then fetches the clean data directly to your chat. No dashboards, no manual clicks.
Using Grepsr MCP lets you control every stage of the data pipeline.
You can list all available reports with 'list_reports' to see what's possible. If a report is set up but never runs, you use 'run_report'. Need to know if it even exists? Check 'get_report_details' before you try anything.
This gives your agent the full context of your data architecture—from initial setup details to final dataset retrieval. It’s centralized control over complex scraping jobs.
What your AI can actually do with this
Imagine needing to track every time a competitor changes its pricing structure. Instead of building custom scripts and managing API keys across multiple services, you connect this MCP and give your AI agent permission to manage all your web scraping jobs. You can tell it to trigger an immediate crawl for a specific site or ask for the 50 most recent records from last week's run.
Your agent handles everything: running the job, tracking its status, retrieving the structured data when it’s ready, and even setting up automated alerts so you know instantly when new information drops into your systems. This gives you total visibility over all your managed scraping operations, letting your AI client act as the central control panel for all your web data feeds.
019d75ab-7aab-728f-b785-cc76c4a25970 Here's how it actually works
The bottom line is that you manage complex data pipelines using natural language prompts in any MCP-compatible client.
First, connect your AI agent by providing your Grepsr API key through Vinkius.
Next, tell your agent what you need—for example, 'Trigger a crawl for the Amazon product report.'
Your agent executes the task, monitors the status, and delivers the resulting structured data directly into your conversation.
Who is this actually for?
This is for engineers and researchers who spend too much time clicking between dashboards just to verify if a script ran or to grab the latest numbers. It’s built for people who need fresh, structured data fast.
Manages crawl statuses and verifies record counts without navigating through multiple web dashboards.
Triggers data refreshes for competitor pricing or product lists directly from the chat interface to capture real-time changes.
Retrieves the latest scraped datasets and confirms delivery integration status automatically when new data is ready.
What Changes When You Connect
You stop manually checking dashboards. By using 'run_report', you trigger a crawl simply by asking your agent, getting fresh data immediately.
Never lose track of what's running again. You can check the full execution history using 'get_report_history' to audit data quality and status instantly.
Setting up alerts is simple. Use 'create_webhook' to ensure that when new data arrives, your internal systems get notified automatically.
You gain total visibility into where your data goes. 'list_integrations' shows you every connected endpoint, including S3 or SFTP.
Need to know what the reports are? Running 'list_reports' gives you a quick inventory of all your configured crawlers in one prompt.
See it in action
Competitor Pricing Monitoring
A market researcher needs daily price data for 50 products. Instead of writing complex scheduled jobs, they tell their agent to 'trigger a crawl' and then ask the agent to fetch structured records using 'get_report_data', ensuring the pricing feed is always current.
Data Pipeline Auditing
An operations team needs to confirm if the data delivery worked last night. They can use 'list_integrations' and then check the run status with 'get_report_history' before notifying stakeholders, guaranteeing reliable reporting.
On-Demand Data Retrieval
A developer needs to validate a specific set of data points immediately. They can ask for the latest items using 'get_latest_data', rather than waiting for the scheduled batch job to run.
System Integration Alerting
A product manager wants their CRM updated instantly when a new report is ready. They use 'create_webhook' to set up a trigger, letting the system handle the notification automatically instead of manual checks.
The honest tradeoffs
Assuming data freshness
Running an analysis on a report and assuming the numbers are current just because it was run yesterday. The data might be stale or incomplete.
Always check the status first by using 'get_report_history' to see when the last successful crawl occurred, then use 'run_report' if needed.
Over-relying on dashboards
Having to click into the Grepsr platform dashboard every time you need a minor status update or dataset verification.
Keep your agent connected. Use 'list_reports' to see what's available and then use specific tools like 'get_report_details' for targeted metadata.
Missing integration visibility
Thinking data was delivered when the connection failed silently, leaving you with no idea if S3 or SFTP received the files.
Use 'list_integrations' to audit all active delivery connections and verify their status before trusting the data.
When It Fits, When It Doesn't
You should use this MCP if your primary job involves extracting, refreshing, or monitoring structured data from external websites. If you need a central command point that lets your AI agent manage multiple scraping projects, check run statuses, and retrieve raw datasets via natural language prompts, this is it. Don't use it if your goal is simply to store documents already in CSV format; for that, you just need a file upload tool. Also, don't rely on it as a replacement for data cleaning—it gets the raw structured data; you still need tools or manual steps to validate integrity and normalize fields.
Questions you might have
How do I see what reports are available with the Grepsr MCP? +
Use 'list_reports'. This tool retrieves a comprehensive list of all your configured crawlers and reports in one go, so you know exactly what data sources exist.
What if I need to update an existing report? Do I use the Grepsr MCP? +
If the crawl is already set up, you just trigger a refresh by using 'run_report'. This tells your agent to run a new instance of the job without changing its core configuration.
Can I check if my data delivery system is working? +
Yes. Use 'list_integrations' to see every active connection (like SFTP or S3) and confirm that your external systems are set up correctly for receiving scraped data.
Is there a tool to get the latest data quickly? +
You can use 'get_latest_data'. This function retrieves the most recent version of a dataset immediately, saving you from having to query deep historical logs.
How do I check my API quota or rate limits using the `get_usage_stats` tool? +
The get_usage_stats tool provides a direct count of your remaining API usage and defined request limits. This tells you exactly how many runs or data queries you have left for the billing period.
If I need specific records, how do I query them using the `get_report_data` tool? +
You use get_report_data by specifying a report ID and the exact fields you want to retrieve. This lets your agent pull only the structured data points you need, rather than massive full datasets.
What is the process for setting up automated alerts using the `create_webhook` tool? +
The create_webhook tool allows you to define a specific URL that Grepsr sends data to immediately after a successful crawl. This bypasses manual checks and notifies your internal systems instantly.
When a crawl fails, how can I diagnose the issue with the `get_report_history` tool? +
The get_report_history tool pulls the full execution log for any report. You can review past runs to see the failure status, error messages, and which steps failed within the scrape process.
Can my agent trigger a new web crawl in Grepsr? +
Yes. Use the 'run_report' tool. By providing the Report ID, the agent can programmatically trigger an on-demand crawl, starting the data extraction process immediately flawlessly.
How do I retrieve the actual scraped data records via chat? +
You can use the 'get_report_data' or 'get_latest_data' tools. Your agent will fetch the structured records from Grepsr's database and present them in a readable format within your chat interface flawlessly.
Can I check my API usage limits through the agent? +
Absolutely. Use the 'get_usage_stats' tool. Your agent will retrieve your current plan limits and remaining API credits, helping you manage your data extraction budget flawlessly.
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