Tools: AutoFinance: Your AI Financial Command Center, right inside the terminal!

Why Leave the Terminal? ## The 13-Server Engine Room ## Key Features ## How GitHub Copilot CLI Saved My Sanity ## 1. The @mcp-server-developer Persona ## 2. Local MCP Integration ## 3. Living Documentation ## Screenshots ## Landing UI ## Dashboard ## Setup in 30 Seconds GitHub Copilot CLI Challenge Submission This is a submission for the GitHub Copilot CLI Challenge As developers, we live in the terminal. So why do we keep switching to 20 different browser tabs just to check market volatility, technical indicators, or portfolio drift? I wanted to see if I could build a professional-grade financial research desk that lives exactly where I do. The result is AutoFinance: a heavy-duty orchestration of 13 specialized MCP (Model Context Protocol) servers that turn your command line into a high-speed financial command center. To power these agents, I stood up 13 microservices using the Model Context Protocol. Each server handles a specific domain: It helped me build this project in less than 36 hours!! (I specifically organized .github/ to leverage Copilot's ability to read configuration files. This ensures every suggestion respects the project's architecture.) Building a system with 13 microservices is not easy. Honestly, if I had to manually manage the boilerplate for every server, I’d still be writing imports. Here is how Copilot CLI helped me: I defined custom instructions so Copilot knew exactly how I wanted my MCP servers structured. When I needed the Volatility Server, I didn't write code; I just talked to my terminal: copilot --agent=mcp-server-developer "Create a volatility server on port 9010 using our standard SSE transport." It generated the Pydantic models and error handling that matched the rest of my stack perfectly. I configured Copilot CLI to actually talk to my running AutoFinance servers. By mapping my local tools in ~/.copilot/mcp-config.json, I could ask the CLI real-time questions: Me: "What's the current RSI for NVDA?" Copilot: "The current RSI for NVDA is 72.4 (Overbought). Recommendation: Wait for a pullback." It bridged the gap between a coding assistant and a production console. Using .github/copilot-instructions.md, I gave Copilot the knowledge of the project—things like port ranges and "no hardcoded API keys" policy. This meant I never had to correct it on the small stuff. It just knew the architecture. I really enjoyed and learnt a lot making this project (plus burnt a lot of credits too :P) made by: crypticsaiyan GitHub Repository: crypticsaiyan/AutoFinance Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse COMMAND_BLOCK: AutoFinance/ ├── .github/ # COPILOT BRAIN 🧠 │ ├── copilot-instructions.md # The "Bible" (Context & Rules) │ ├── mcp-config.json # Local MCP Server Config │ ├── agents/ # Specialized Personas │ │ ├── mcp-server-developer.md │ │ ├── financial-analyst.md │ │ ├── cli-dashboard-dev.md │ │ └── test-engineer.md │ ├── skills/ # Reusable Knowledge │ │ ├── financial-data-validation/ │ │ ├── mcp-server-debugging/ │ │ └── technical-analysis-impl/ │ ├── instructions/ # Path-Specific Context │ │ ├── mcp-servers.md │ │ └── tests.md │ └── hooks/ # Automation Scripts │ └── hooks.json # Pre/Post-execution logic ├── mcp-servers/ # THE 13 MICROSERVICES │ ├── market/ # Yahoo Finance Integration │ ├── technical/ # RSI/MACD/Bollinger Logic │ ├── sentiment/ # NewsAPI + LLM Analyzer │ ├── risk/ # Compliance & Limits Engine │ └── ... (10 others) └── cli/ # The Textual Dashboard UI Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: AutoFinance/ ├── .github/ # COPILOT BRAIN 🧠 │ ├── copilot-instructions.md # The "Bible" (Context & Rules) │ ├── mcp-config.json # Local MCP Server Config │ ├── agents/ # Specialized Personas │ │ ├── mcp-server-developer.md │ │ ├── financial-analyst.md │ │ ├── cli-dashboard-dev.md │ │ └── test-engineer.md │ ├── skills/ # Reusable Knowledge │ │ ├── financial-data-validation/ │ │ ├── mcp-server-debugging/ │ │ └── technical-analysis-impl/ │ ├── instructions/ # Path-Specific Context │ │ ├── mcp-servers.md │ │ └── tests.md │ └── hooks/ # Automation Scripts │ └── hooks.json # Pre/Post-execution logic ├── mcp-servers/ # THE 13 MICROSERVICES │ ├── market/ # Yahoo Finance Integration │ ├── technical/ # RSI/MACD/Bollinger Logic │ ├── sentiment/ # NewsAPI + LLM Analyzer │ ├── risk/ # Compliance & Limits Engine │ └── ... (10 others) └── cli/ # The Textual Dashboard UI COMMAND_BLOCK: AutoFinance/ ├── .github/ # COPILOT BRAIN 🧠 │ ├── copilot-instructions.md # The "Bible" (Context & Rules) │ ├── mcp-config.json # Local MCP Server Config │ ├── agents/ # Specialized Personas │ │ ├── mcp-server-developer.md │ │ ├── financial-analyst.md │ │ ├── cli-dashboard-dev.md │ │ └── test-engineer.md │ ├── skills/ # Reusable Knowledge │ │ ├── financial-data-validation/ │ │ ├── mcp-server-debugging/ │ │ └── technical-analysis-impl/ │ ├── instructions/ # Path-Specific Context │ │ ├── mcp-servers.md │ │ └── tests.md │ └── hooks/ # Automation Scripts │ └── hooks.json # Pre/Post-execution logic ├── mcp-servers/ # THE 13 MICROSERVICES │ ├── market/ # Yahoo Finance Integration │ ├── technical/ # RSI/MACD/Bollinger Logic │ ├── sentiment/ # NewsAPI + LLM Analyzer │ ├── risk/ # Compliance & Limits Engine │ └── ... (10 others) └── cli/ # The Textual Dashboard UI COMMAND_BLOCK: git clone https://github.com/crypticsaiyan/AutoFinance.git pip install -r mcp-servers/requirements.txt pip install -r cli/requirements.txt ./start_sse_servers.sh # Fire up the 13-server swarm python cli/main.py # Launch the Command Center # see the repo for more advanced setup Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: git clone https://github.com/crypticsaiyan/AutoFinance.git pip install -r mcp-servers/requirements.txt pip install -r cli/requirements.txt ./start_sse_servers.sh # Fire up the 13-server swarm python cli/main.py # Launch the Command Center # see the repo for more advanced setup COMMAND_BLOCK: git clone https://github.com/crypticsaiyan/AutoFinance.git pip install -r mcp-servers/requirements.txt pip install -r cli/requirements.txt ./start_sse_servers.sh # Fire up the 13-server swarm python cli/main.py # Launch the Command Center # see the repo for more advanced setup - 📈 Real-Time Market Data: Connects directly to Yahoo Finance and Binance (via WebSockets) to stream live prices. No staleness—just raw, real-time data. - 📡 Multi-Channel Global Notifications: Never miss a beat. The system pushes critical alerts to where you actually live: Slack & Discord: Get trade confirmations, price spikes, and agent debates in your channels. SMS & WhatsApp: Urgent margin calls or crash alerts sent directly to your phone. Email: Daily portfolio summaries and audit reports. - Slack & Discord: Get trade confirmations, price spikes, and agent debates in your channels. - SMS & WhatsApp: Urgent margin calls or crash alerts sent directly to your phone. - Email: Daily portfolio summaries and audit reports. - 🛡️ Automated Risk Guardrails: The Risk Server enforces strict position limits (max 5%) and stop-losses automatically. It rejects any trade that violates your pre-set safety policy. - 💬 Natural Language Interface: Deep copilot CLI integration lets you "chat" with your portfolio. "Hey, sell half my Bitcoin if RSI > 80." - 📊 Comprehensive Analysis: Technical: Real-time RSI, MACD, and Bollinger Bands. Fundamental: P/E ratios, ROE, and growth metrics. Sentiment: Scans news headlines to gauge the current market mood. - Technical: Real-time RSI, MACD, and Bollinger Bands. - Fundamental: P/E ratios, ROE, and growth metrics. - Sentiment: Scans news headlines to gauge the current market mood. - Slack & Discord: Get trade confirmations, price spikes, and agent debates in your channels. - SMS & WhatsApp: Urgent margin calls or crash alerts sent directly to your phone. - Email: Daily portfolio summaries and audit reports. - Technical: Real-time RSI, MACD, and Bollinger Bands. - Fundamental: P/E ratios, ROE, and growth metrics. - Sentiment: Scans news headlines to gauge the current market mood.