Build Serverless Data Warehouses Using MCP.
You scrape data into CSV files that nobody queries , Firecrawl extracts structured web data, Neon stores it in serverless PostgreSQL you can query with SQL, and Sheets visualizes the results
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your agent builds a data warehouse from the web. Step 1: Firecrawl scrapes structured data , product listings, pricing, company information, job postings , from target websites.
Handles JavaScript, pagination, and complex site structures. Step 2: Neon creates a PostgreSQL database with proper schemas: CREATE TABLE products (id, name, price, category, source_url, scraped_at).
Indexes on price, category, scraped_at. The data goes into a real database , not a CSV, not a JSON file, not a Google Sheet.
A proper relational database you can query with SQL. Step 3: SQL queries extract insights. 'Average price by category this month vs last month' runs as a real SQL query with JOINs, GROUP BYs, and window functions.
Results go to Sheets as an analytical dashboard. The database scales to zero when idle , you pay nothing when you are not querying.
Connector Orchestration: 3 Connectors, one intelligent agent
Connect Neon, Firecrawl and Google Sheets so your AI agent scrapes structured data from any website using Firecrawl, stores it in a Neon serverless PostgreSQL database with proper schemas and indexes, and builds analytical dashboards in Sheets from SQL queries.
Neon Serverless Postgresql
actionServerless PostgreSQL that scales to zero , stores scraped data in proper relational schemas with full SQL query power
run_sql list_databases list_tables describe_table get_connection_string Firecrawl
triggerExtracts structured data from any website , handles JavaScript rendering, pagination and anti-bot measures
scrape_url crawl_url search extract_data check_crawl_status Google Sheets
enrichmentVisualizes SQL query results as analytical dashboards and reports
create_spreadsheet update_sheet_values append_sheet_values get_sheet_values Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own Connector
Convert any internal API into a Connector. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Neon Serverless Postgresql, Firecrawl & Google Sheets ready in the catalog right now
- Add more from 5,800+ servers whenever you need
- Connections are secured and compliant by default
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added weekly
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 5,800+ Connectors and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across all tools, in one conversation. That's what this connectivity layer was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across all platforms.
Contextual Reasoning
Each decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your Connectors once, and your agent handles the rest. Each time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius AI Connectors to handle these for you. You describe what you need. It does the rest.
AI builders creating queryable databases from web data without managing database infrastructure
Researchers building longitudinal datasets from web scraping with SQL-powered analysis
Product teams tracking competitor pricing in a real database instead of spreadsheets
AI enthusiasts building personal data warehouses from niche web sources with zero DevOps
Frequently Asked Questions About This Connector Orchestration
Which Connectors do I need?
Three: Neon, Firecrawl and Google Sheets.
Does this work with Claude Desktop?
Yes. Any MCP-compatible AI client works.
Does Neon really scale to zero?
Yes. Neon serverless PostgreSQL suspends after inactivity and resumes in ~500ms on next query. Zero cost when idle.
Is my data secure?
Connectors authenticate via API keys. Neon stores data in your database. Firecrawl scrapes public web content.
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Connectors used in this workflow
Neon (Serverless PostgreSQL)
Neon (Serverless PostgreSQL) MCP. Manage your serverless database infrastructure, handle zero-copy branching, audit projects, and monitor compute endpoints directly through your AI agent.
Firecrawl
Firecrawl turns any website into clean Markdown for your AI agents. It handles the messy parts of web scraping like JavaScript rendering and anti-bot protections, so your agent gets structured data instead of a wall of HTML. It's built for high-quality data extraction at scale.
Google Sheets
Google Sheets MCP lets you read, write, and manage spreadsheet data through your AI agent. Stop wasting time on manual data entry or complex formulas. Just tell your agent to pull specific ranges, add new rows, or create entire new sheets on the fly. It handles the tedious work of keeping your data organized so you can focus on making decisions.