DevFestIca25-Activity1

This MCP server automates the workflow of turning a requirements document into actionable GitHub issues and a backlog plan. It leverages GitHub Copilot and MCP (Model Context Protocol) to parse requirement files (such as project/requirements.md) and generate well-described issues with complexity labels, then helps organize work in GitHub Projects. You can interact with the server to analyze documents, produce an issue_create command, and push code changes to a new branch for each resolved task. The workflow is designed to be used either from the terminal with Copilot CLI commands or via a Copilot Chat integration in VS Code, enabling natural-language prompts to drive issue creation and code generation.

Once the server is running, you can:

• Analyze a requirements file to extract tasks and convert them into GitHub issues with clear descriptions and estimated complexity labels.
• Trigger generation of code changes or project scaffolding in a new branch to address each issue, integrating with your GitHub repository workflows.
• Use Copilot prompts in the terminal or within VS Code to request analysis, issue creation, and subsequent code generation or branch creation, streamlining the end-to-end automation of project tasks.

Prerequisites:

• Docker installed and running on your machine or host where the MCP server will run.
• GitHub access with permissions to create issues, labels, and branches in the target repository.
• Optional: GitHub Copilot CLI or Copilot for VS Code if you plan to interact with Copilot directly.

Installation steps (Docker-based):

1. Ensure Docker is running on your system.
2. Pull or build the MCP server image (example using the provided image name in this repository): docker pull dav082004/devfestica25-activity1-server
3. Run the MCP server container in interactive mode compatible with MCP expectations: docker run -it --rm -p 8080:8080 -e MCP_TOKEN=<your-token> -e OPENAI_API_KEY=<your-openai-key> dav082004/devfestica25-activity1-server
4. Validate the server is reachable on the configured port (default 8080) and that it exposes the MCP endpoints.

Alternative (if you have a local Node/Python setup in your environment):

• If a local server script is provided, install dependencies and run the server with the appropriate command shown in the repository (for example, node server.js or python -m mcp_server). Adjust the mcp_config accordingly.

Notes:

• Replace placeholder environment variables (MCP_TOKEN, OPENAI_API_KEY) with your actual credentials or tokens as required by the server.
• Ensure network access between the MCP server and your GitHub repository for creating issues and pushing branches.

Tips and common considerations:

• Keep your GitHub repository permissions in mind: the MCP server will create issues, labels, and branches, so ensure the token used has sufficient scopes (repo, issues, pull_request, contents).
• If you encounter rate limits from GitHub or the Copilot API, implement simple retry/backoff strategies and consider staggering automated tasks.
• Define a consistent labeling strategy for complexity (e.g., labels like bug, enhancement, complexity:low/medium/high) to ensure predictable backlog organization.
• If you customize the prompts, test them against a small sample requirements document to verify the generated issues meet your expectations before scaling.
• Maintain environment variable security: use secret management for API keys and tokens where possible.