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Apoorv Gupta
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Stock Search and Insights Using Algolia and n8n

#algoliachallenge #ai #bunjs #n8n

Algolia MCP Server Challenge: Backend Data Optimization

This is a submission for the Algolia MCP Server Challenge

Stock Search & Insights Platform

What I Built

I built a Stock Search & Insights Platform powered by the Algolia MCP Server for blazing-fast symbol and company name lookups.

  • Algolia provides instant search across an index of stock names and symbols.
  • Bun serves as the lightweight backend to fetch data and interact with external APIs.
  • n8n acts as an orchestration backend, managing workflows for technical analysis, AI-driven insights, and data enrichment.
  • TwelveData APIs are used for fetching real-time prices, technical analysis, and SMA calculations.
  • Chart-IMG API generates advanced charts with Bollinger Bands, RSI, and Volume indicators.
  • GPT‑4o‑mini analyzes the data and produces quick, AI-driven insights for each stock.

The result: A single interface where users can search for a stock, instantly view real-time price data, AI-powered analysis, and technical charts — all in one place.

Demo

How I Utilized the Algolia MCP Server

  • Built an Algolia MCP Server to manage and query a custom stock index containing symbols, company names, and exchanges.
  • Exposed MCP-like endpoints (/mcp/searchStocks, /mcp/analyzeStock) that act as a single entry point for the frontend, abstracting away multiple API calls and complex workflows.
  • Integrated Algolia InstantSearch with my React frontend for fast, typo-tolerant, and responsive search.
  • Used the MCP server as a broker between Algolia, n8n workflows (for chart generation, technical analysis, and AI insights), and external APIs (TwelveData & Chart-IMG).
  • This architecture decouples the frontend from multiple data sources — the MCP server handles enrichment, error handling, and data aggregation before sending a unified response back to the UI.

Key Takeaways

  • Performance is key: Algolia MCP made stock searching instantaneous, which is crucial for a financial data app.
  • Workflow automation saves time: n8n helped me orchestrate data fetching (real-time quotes, SMA, technical indicators) and combine them into a single response for the frontend.
  • AI adds value: Using GPT‑4o‑mini, I transformed raw numbers into actionable insights for end-users.
  • Charting matters: Integrating Chart-IMG allowed me to display professional-grade charts with key indicators effortlessly.
  • Learned how to combine Algolia + MCP + Bun + n8n + React + AI into a cohesive product pipeline.

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