> ## Documentation Index > Fetch the complete documentation index at: https://docs.dataville.com/llms.txt > Use this file to discover all available pages before exploring further. # Build a Langflow Agent with SEC EDGAR and Wikipedia > Build a Langflow AI research agent using Dataville's MCP server to combine SEC EDGAR financial filings with Wikipedia company information. A company research agent needs more than a plausible summary. It needs financial figures tied to a reporting period, company background from an identifiable source, and links you can follow to check its claims. We'll build one in Langflow using Dataville's MCP server. Using Walmart as our example, we'll combine Wikipedia context with SEC EDGAR filings, generate a cited report, and inspect the tool responses to see where the numbers and dates came from. Want to run the example first? The [companion repository](https://github.com/datavilleorg/langflow-company-research) includes the flow, agent instructions, and a sample report. The demo video builds the flow in this guide, from the **Simple Agent** template to the finished Walmart report. Before it ends, it opens Walmart's 10-K on the SEC website to check the figures in the report.