README.md

---
title: Deploy Ready Copilot
emoji: 🚀
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
tags:
  - mcp-in-action-track-enterprise
  - building-mcp-track-enterprise
  - gradio
  - claude
  - multi-agent
  - deployment
  - productivity
  - context7
  - github
  - vercel
  - mcp-server
---

# 🚀 Deployment Readiness Copilot

**Multi-agent AI system for deployment readiness validation and documentation generation**

## 🎯 Overview

The Deployment Readiness Copilot is a productivity-focused, developer-centric tool that automates deployment readiness checks using a multi-agent architecture. It combines Claude's reasoning with sponsor LLM cross-checks and MCP tool integration to provide comprehensive pre-deployment validation across multiple platforms.

## ✨ Features

- **🤖 Multi-Agent Pipeline**: Planner → Evidence Gatherer → Synthesis → Documentation → Reviewer → Docs Lookup → Deployment
- **📁 Codebase Analysis**: Upload folder (ZIP) or GitHub repo → Auto-detect framework, dependencies, configs
- **📚 Context7 Documentation Integration**: Automatic framework/platform documentation lookups
- **🔧 MCP Tool Integration**: Real-time deployment signals from Hugging Face Spaces, Vercel, Context7, and GitHub
- **🚀 Multi-Platform Deployment**: Deploy to Vercel, Netlify, AWS, GCP, Azure, Railway, Render, Fly.io, Kubernetes, Docker
- **🎓 Sponsor LLM Cross-Checks**: Gemini 2.0 Flash + OpenAI GPT-4o mini for synthesis and validation
- **📝 Auto-Documentation**: Generates changelog entries, README snippets, and announcement drafts
- **✅ Risk Assessment**: Automated review with confidence scoring and actionable findings

### 🔥 10 Major Utility Improvements

1. **📊 Real-Time Deployment Monitoring**: Track deployment status, stages, and logs in real-time
2. **🔒 Security Scanning**: Scan dependencies for vulnerabilities and detect exposed secrets
3. **💰 Cost Estimation**: Compare costs across platforms with optimization recommendations
4. **🔐 Environment Variable Validation**: Validate env vars, detect missing required vars, security issues
5. **⚡ Performance Optimization**: Framework-specific performance analysis and improvement suggestions
6. **🔄 CI/CD Pipeline Generation**: Auto-generate GitHub Actions and GitLab CI configurations
7. **⏮️ Rollback Strategies**: Generate rollback plans and disaster recovery procedures
8. **🌍 Multi-Environment Support**: Deploy to dev/staging/production with environment-specific configs
9. **👥 Team Collaboration**: Review sessions, stakeholder approvals, comments, and feedback
10. **📊 Monitoring Integration**: Setup recommendations for Sentry, New Relic, Datadog, and platform-native tools

## 🏗️ Architecture

### Agents

1. **Planner Agent (Claude)**: Analyzes project context and generates deployment readiness checklist
2. **Evidence Agent (Claude + MCP)**: Gathers real deployment signals via MCP tools
3. **Synthesis Agent (Gemini/OpenAI)**: Cross-validates Claude's evidence to earn sponsor bonus points
4. **Documentation Agent (Claude)**: Generates deployment communications
5. **Reviewer Agent (Claude)**: Final risk assessment with confidence scoring
6. **Documentation Lookup Agent (Context7)**: Looks up framework/platform docs for:
   - Deployment guides
   - Dependency compatibility
   - Config validation
   - Runbook generation
   - Environment variables
   - Migration guides
   - Observability setup
7. **Deployment Agent (GitHub)**: Prepares and executes deployment actions

### MCP Tools Used

- **Context7**: Framework/platform documentation lookups
- **Hugging Face Spaces**: Status checks and validation
- **Vercel**: Deployment validation
- **GitHub**: Deployment PR creation and workflow triggers
- (Extensible to other MCP-compatible services)

## 🚀 Quick Start

1. **Set Environment Variables** (in HF Space Secrets):
   - `ANTHROPIC_API_KEY`: Your Claude API key (required)
   - `GOOGLE_API_KEY` or `GEMINI_API_KEY`: Enables Gemini sponsor synthesis
   - `OPENAI_API_KEY`: Enables OpenAI sponsor synthesis
   - `SPONSOR_LLM_PRIORITY`: Optional override (default `gemini,openai`)
   - `GEMINI_MODEL`, `OPENAI_MODEL`: Optional model overrides
   - `HF_TOKEN`: For Hugging Face MCP tools (optional)
   - `GITHUB_TOKEN`: For GitHub deployment actions (optional)
   - `GITHUB_REPO`: Repository in format `owner/repo` (optional, for deployments)
   - `GITHUB_BRANCH`: Branch name (default: `main`) (optional)

2. **Upload & Analyze**:
   - Upload your project folder as ZIP, OR
   - Enter GitHub repo URL
   - Click "Analyze Codebase" to auto-detect framework and dependencies

3. **Configure & Deploy**:
   - Review auto-filled project details
   - Select deployment platform (Vercel, AWS, etc.)
   - Choose environment (dev/staging/production)
   - Click "Run Full Pipeline & Deploy"
   - Review all utility reports (security, cost, performance, etc.)
   - Deploy directly via MCP

## 📋 Example Usage

```
Project: Telemetry API
Release Goal: Enable adaptive sampling
Code Summary: Adds config surface, toggles feature flag, bumps schema version.
Stakeholders: eng, sre
```

The system will:
1. Generate a deployment readiness plan
2. Gather evidence via MCP tools
3. Lookup framework/platform documentation via Context7
4. Cross-validate evidence with sponsor LLMs
5. Create documentation artifacts
6. Prepare GitHub deployment actions (if configured)
7. Provide final review with risk assessment

## 🎯 Hackathon Submission

**Primary Tracks**: 
- `mcp-in-action-track-enterprise` (MCP in Action - Enterprise)
- `building-mcp-track-enterprise` (Building MCP - Enterprise)

**Multi-Track Compatibility**:
- ✅ **Track 1 (Building MCP)**: Functions as an MCP server with custom tools.
- ✅ **Track 2 (MCP in Action)**: Autonomous multi-agent behavior with planning, reasoning, and execution via MCP tools.
- ✅ **LlamaIndex Prize**: Integrated `RAGAgent` using LlamaIndex for codebase analysis.
- ✅ **OpenAI/Gemini Prizes**: Uses OpenAI and Gemini for sponsor cross-checks.

**Key Highlights**:
- ✅ Autonomous multi-agent behavior with planning, reasoning, and execution
- ✅ MCP servers used as tools (Context7, HF Spaces, Vercel, GitHub)
- ✅ Context7 integration for comprehensive documentation lookups
- ✅ GitHub deployment actions for direct deployment execution
- ✅ Gradio app with MCP server support (`mcp_server=True`)
- ✅ Sponsor LLM integration (Gemini, OpenAI) with configurable priority
- ✅ Real-world productivity use case for developers
- ✅ 10 utility improvements covering security, cost, performance, CI/CD, monitoring, and collaboration

## 🔧 Technical Stack

- **Gradio 5.49.1**: UI framework with MCP server support
- **Anthropic Claude 3.5 Sonnet**: Primary reasoning engine
- **Google Gemini 2.0 Flash**: Sponsor cross-validation
- **OpenAI GPT-4o mini**: Alternate sponsor cross-validation
- **Hugging Face Hub**: MCP client for tool integration
- **Context7 MCP**: Documentation lookup service
- **GitHub & Vercel MCP**: Deployment validation and workflow triggers
- **LlamaIndex**: RAG engine for codebase analysis
- **Python 3.10+**: Core runtime

## 🔐 Secrets & API Keys

Add secrets in Hugging Face Space → **Settings → Repository secrets**:

| Secret | Purpose |
| --- | --- |
| `ANTHROPIC_API_KEY` | Required for Claude agents |
| `GOOGLE_API_KEY` / `GEMINI_API_KEY` | Enable Gemini sponsor synthesis |
| `OPENAI_API_KEY` | Enable OpenAI sponsor synthesis |
| `SPONSOR_LLM_PRIORITY` | Optional ordering, e.g. `gemini,openai` |
| `GEMINI_MODEL`, `OPENAI_MODEL` | Optional model overrides |
| `HF_TOKEN` | Optional Hugging Face MCP access |
| `GITHUB_TOKEN`, `GITHUB_REPO`, `GITHUB_BRANCH` | GitHub deployment actions |

## 📝 License

MIT License

## 🔗 Social Media

[Link to your social media post about the project] <!-- REQUIRED: Add your LinkedIn/X post link here -->

## 🎥 Demo Video
[Link to your demo video] <!-- REQUIRED: Add your demo video link here -->

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**Built for MCP's 1st Birthday Hackathon** 🎉