"How to interact with Notion" matching MCP connectors:
Matching Connector Tools:
Search live job postings from 30+ ATS feeds and job boards, normalized to one schema.
Scrapingdog MCP — wraps Scrapingdog (scrapingdog.com), a proxy-based web
Auto-discover validation rules from data — scan, profile, health-score. No rules to write.
Query, join, profile, clean and convert CSV/JSON/Parquet with server-side DuckDB over MCP.
Excel analytics: inspect, query (JSON rows), charts, and JSON-to-xlsx workbook writing.
Live data gateway for AI — 3,300+ tools across 750+ sources, with citations
297 data tools across 90 MCP servers via one gateway. Free trial header; x402 USDC on Base.
AI access to Quadratic spreadsheets: open files, run Python/SQL, query connected databases.
Self-hosted, open-source MCP gateway: turn any API, database or MCP server into custom connectors for Claude, ChatGPT, Gemini, Copilot & Cursor — no code. Converts REST, SOAP, WSDL, GraphQL & SQL to MCP, with OAuth2, RBAC & audit log. 175+ pre-built adapters. This is the public read-only demo endpoint — run your own at https://github.com/HelpCode-ai/anythingmcp
Connect your Nubank account to AI via Brazil's Open Finance: balances, statements, cards, investment
DBnomics MCP — meta-aggregator over 80+ stats providers
Baselight’s MCP server lets you seamlessly integrate your favourite applications with the Baselight platform. By connecting to the MCP server, you can browse, discover, and query 70,000+ datasets and 450+ billion rows directly from your preferred environment—whether you’re building, analysing, or exploring.
Interact with your Google Cloud Datastream resources using natural language commands.
Document processing, data conversion, and web content APIs for AI agents. All tools are free via MCP. Also available as a paid x402 Agent API (Stellar XLM or Solana USDC, no API key required). Tools: extract text from PDFs, merge PDFs, generate QR codes, convert CSV to/from JSON, count words/stats, and fetch + clean any public URL with Mozilla Readability.
Schema modeling in JSON, JSON-LD, and other formats with CoreModels platform.
Turn documents into structured, AI-ready data by parsing, enriching, chunking, and embedding.
Map messy columns to a known schema — 7 scorers, domain dictionaries, F1 0.84. Zero config.