README.md

metadata

title: SEC10QInsight
emoji: ⚡
colorFrom: purple
colorTo: indigo
sdk: gradio
sdk_version: 5.33.0
app_file: app.py
pinned: false
license: mit
short_description: SEC 10-Q data explorer with AI insights
tags:
  - mcp-server-track
  - agent-demo-track
  - gradio-mcp-server
  - sec-10q
  - financial-insight

📘 SEC10QInsight – A Gradio-Based MCP Server for SEC Financial Analysis

🔍 Overview – SEC10QInsight: Agentic SEC Data Analyst

👉 Jump to: Try It Yourself ⬇️

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🎥 Demo Video

▶️ Watch the full demo on YouTube:
https://youtu.be/vin-Ovz2sFI?si=9n1kIcgnNs-b2K8d

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SEC10QInsight is an interactive MCP (Model Context Protocol) server built with Gradio that empowers users to query, visualize, and interpret financial data extracted from SEC 10-Q filings. Leveraging the power of large language models (LLMs), SEC10QInsight translates raw financial disclosures into insightful summaries, trend analysis, and visual dashboards.

Built with Gradio and powered by the Model Context Protocol (MCP), this app simulates a multi-step agent process:

1. Retrieve real-time financial data from the SEC EDGAR database using a CIK (Central Index Key)
2. Structure and filter relevant metrics (e.g., ComprehensiveIncomeNetOfTax)
3. Visualize historical trends using line plots
4. Analyze the data using a large language model (LLM) to generate concise insights

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🎯 Purpose

This app demonstrates how agentic workflows can be applied to financial intelligence, allowing a single natural language query to trigger a multi-step, automated reasoning process that includes:

• Data retrieval (from SEC)
• Contextual structuring and preprocessing
• Visualization
• LLM-driven interpretation

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🔑 Key Features

• 🔍 Natural language querying of SEC data (e.g., "Show trends")
• 📊 Interactive data visualization of quarterly metrics like Comprehensive Income
• 🤖 LLM-powered financial insights, integrated with models like SambaNova
• 🌐 Live data fetching from the SEC's EDGAR API (XBRL format)
• ⚙️ Gradio UI for clean, user-friendly access to analysis tools

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🛠️ Usage

1. Select a company (Apple, Tesla, Microsoft) (The sample here for HF MCP Hachathon specifically)
2. Enter a query, such as:
   • "Summarize the trend"
   • "How did income change over time?"
3. Submit the query
4. The app will:
   • Fetch SEC 10-Q data
   • Display it in a table
   • Render a trend plot
   • Return a model-generated interpretation

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🤖 Agentic Highlights

• Autonomous orchestration of data + language processing
• Modular architecture with MCP for easy extensibility
• Real-world grounding using factual data from SEC filings

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SEC10QInsight is ideal as a reference project or demo for:

• Agentic LLM workflows
• Financial data applications
• LLM × structured data integrations

Ideal for researchers, analysts, developers, and AI enthusiasts, SEC10QInsight demonstrates how open financial data and cutting-edge AI can work together to deliver explainable, real-time insights.

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🚀 Try It Yourself

Users can try this amazing MCP server by accessing the client and code here:
👉 SEC10QInsight-MCP-CLIENT on Hugging Face Spaces

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📦 Tech Stack

• Python
• Gradio
• Pandas & Matplotlib
• SEC EDGAR API (XBRL JSON)
• OpenAI-compatible LLM client (e.g., SambaNova)
• MCP (Model Context Protocol)

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📜 License

MIT License — open for learning, building, and extending.

Perfect for exploring how LLMs can assist in structured financial analysis through agentic design!