𝐁𝐮𝐢𝐥𝐝 𝐀𝐈 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐰𝐢𝐭𝐡 𝐌𝐂𝐏 𝐒𝐞𝐫𝐯𝐞𝐫𝐬 + 𝐧𝟖𝐧

𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 - 𝐥𝐢𝐯𝐞 𝐚𝐩𝐩 𝐚𝐭 mcp.tigzig.com - 𝐨𝐩𝐞𝐧 𝐬𝐨𝐮𝐫𝐜𝐞

The app generates tech indicators from Yahoo Finance price data, feeds into Gemini Vision for AI chart analysis, and outputs as PDF + web reports. Powered by custom-built plug-and-play MCP servers on the backend.

This setup was made possible by recent releases from Tadata and n8n. Tadata’s FastAPI-MCP lets you turn any FastAPI into an MCP server in just a few lines of code, with both servers live in a single deployment... and n8n’s new MCP Client node connects instantly to any SSE-based MCP server - elegant and powerful tools.

I use FastAPI extensively for both agentic and non-agentic workflows. The ease of use, flexibility, and reusability is huge with MCP. My integrated FastAPI-MCP server run on a Docker-containerized setup and are now connected to AI Agents, n8n, Flowise, a form-based Flask UI, and Excel via xlwings Lite. Previous posts cover these, with live apps and source codes on site.

Yes, MCP has vulnerabilities, and I am still battle testing it ... but the ecosystem is evolving fast - and solutions are coming up as we speak.

I've made the MCP servers public - clone or connect directly. Head over to mcp.tigzig.com for server URLs, tech setup, how it works, n8n schema, and full source code with build guides.

Huge thanks to the Tadata team - Shahar Abramov, Tori Seidenstein, Michael Makhlevich, Itay Shemer - for a solid product and for pushing enhancements at a rapid pace …the recent httpx client dependency injection for timeout handling made a big difference in getting this setup running.

FastAPI MCP GitHub Repo: https://lnkd.in/gNSTQfpN

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Note: This is not investment advice or investment research, but a tech example on how to combine AI, MCP and analytics workflows.