Add project description in the readme file
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# capstone_msagi
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Product Strategy Simulation
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Course-end Project: Product Strategy Simulation
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Multi-Agent Market Research and GTM Planning (n8n, MCP, and CrewAI)
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Description
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Overview
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In this project, you will design and implement a multi-agent workflow system that automates market research and go-to-market (GTM) planning. The systems are implemented in n8n and CrewAI separately, but with similar functionality. The solution integrates four agents:
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• Head Planner (orchestrator and documenter)
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• Research Agent (finder)
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• Analyst Agent (sense-maker)
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• Strategy Agent (planner)
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The workflow must orchestrate desk research, competitor analysis, and GTM plan drafting before exporting structured strategy documents to Google Docs.
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Instructions
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• Review the lessons and supporting materials on n8n workflows, MCP, and CrewAI
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• Set up the required environment on the Ubuntu VM, including Node.js, n8n, and Python for CrewAI
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• Execute the following steps:
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Build the multi-agent orchestration with a Head Planner and three specialist agents with tools
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Start the MCP server
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Configure and connect the n8n workflow with the MCP
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Implement CrewAI with defined agents, flows, and tools (MCP, SerpAPI)
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• Test and debug each component individually (MCP tools with curl, n8n nodes with Execute Node, and CrewAI tasks end-to-end)
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• Document the architecture, configuration steps, test runs, and error resolutions
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• Submit the following:
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Exported n8n workflow JSON file
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CrewAI project files (UV structure)
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Sample Google Doc output
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CrewAI chatbot screenshots
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Documentation (README file) covering the architecture, setup, and testing notes
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