Business Proposal Agent

DealPilot — AI Sales Proposal Agent

Google Cloud Rapid Agent Hackathon · MongoDB Partner Track

DealPilot is an autonomous AI sales agent that turns discovery call transcripts into winning business proposals. It analyzes client needs, searches similar past projects in MongoDB Atlas, generates a tailored proposal with Gemini, and saves results for future reuse.

Built with Google ADK (Agent Builder), Gemini, and MongoDB MCP integration.

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Demo flow

1. Paste a discovery call transcript (or click Load sample).
2. The agent runs a transparent 3-step pipeline:

• Step 1 — Analyzer: Extract industry, company size, pain points, timeline, budget.
• Step 2 — Researcher: Query MongoDB for similar historical projects.
• Step 3 — Generator: Write an 800–1200 word professional proposal.

1. View results as plain text or export a PDF via the Anvil API.
2. Proposals are auto-saved to MongoDB Atlas.

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Architecture

flowchart LR
    UI[Next.js Frontend :3000]
    ADK[Google ADK Agent :8080]
    MCP[MongoDB MCP Server]
    API[FastAPI Backend :8000]
    DB[(MongoDB Atlas)]

    UI -->|chat / run| ADK
    UI -->|save proposal| API
    ADK --> MCP
    MCP --> DB
    API --> DB
    UI -->|PDF export| Anvil[Anvil PDF API]

| Layer | Technology | Port | |-------|------------|------| | Frontend | Next.js 16, React 19, Tailwind CSS 4 | 3000 | | Agent | Google ADK (dealpilot) + Gemini | 8080 | | MCP | FastMCP server → MongoDB Atlas | stdio | | Backend | FastAPI (save API + fallback pipeline) | 8000 | | Database | MongoDB Atlas proposaldb | cloud |

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Features

• Multi-step agentic pipeline — plans and executes analyze → research → generate under user oversight
• MongoDB MCP tools — search projects, save proposals, list recent proposals, aggregate stats
• Chat UI — ADK-style interface with tool-call visibility and quick prompts
• Auto-save — generated proposals persist to the proposals collection
• Dual output — plain-text proposal or PDF download (Anvil)
• Fallback mode — FastAPI 3-step Gemini pipeline when ADK is unavailable

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Prerequisites

• Python 3.11+
• Node.js 20+
• MongoDB Atlas cluster (free tier works)
• Google AI Studio API key (Gemini)
• Anvil API key (optional — PDF export; dev key is free with watermark)

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Quick start

1. Clone and configure

git clone https://github.com/AaronTide/business-proposal-agent.git
cd business-proposal-agent

Copy environment files and add your keys:

# Backend
copy backend\.env.example backend\.env

# Agent
copy agent\dealpilot\.env.example agent\dealpilot\.env

# Frontend
copy frontend\.env.local.example frontend\.env.local

2. Backend setup

cd backend
python -m venv .venv
.\.venv\Scripts\pip install -r requirements.txt
.\.venv\Scripts\python seed_db.py

3. Agent setup

cd agent
.\scripts\start_agent.ps1

Opens the ADK web UI at http://127.0.0.1:8080 — select dealpilot from the dropdown.

4. Start backend API (MongoDB save)

In a new terminal:

cd backend
.\.venv\Scripts\uvicorn main:app --reload --port 8000

5. Start frontend

In a new terminal:

cd frontend
npm install
npm run dev

Open http://localhost:3000

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Environment variables

backend/.env

| Variable | Description | |----------|-------------| | GEMINI_API_KEY | Google AI Studio API key | | GEMINI_MODEL | Default: gemini-2.5-flash | | MONGODB_URI | MongoDB Atlas connection string | | MONGODB_DATABASE | Default: proposaldb |

agent/dealpilot/.env

| Variable | Description | |----------|-------------| | GOOGLE_API_KEY | Gemini API key for ADK | | GOOGLE_GENAI_USE_VERTEXAI | FALSE for AI Studio, TRUE for Vertex AI | | MDB_MCP_CONNECTION_STRING | MongoDB Atlas URI (official MCP variable name) | | MONGODB_DATABASE | Default: proposaldb | | GEMINI_MODEL | Default: gemini-2.5-flash |

frontend/.env.local

| Variable | Description | |----------|-------------| | ADK_AGENT_URL | ADK agent URL (default http://127.0.0.1:8080) | | ADK_APP_NAME | Agent name: dealpilot | | USE_ADK_AGENT | true = ADK agent, false = FastAPI fallback | | BACKEND_URL | FastAPI URL for MongoDB save (default http://127.0.0.1:8000) | | ANVIL_API_KEY | Anvil PDF generation API key |

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MongoDB MCP tools

The agent connects to MongoDB via a custom MCP server at backend/mcp_server.py:

| Tool | Purpose | |------|---------| | search_similar_projects | Find past projects by industry | | find_documents | Query any collection with a filter | | save_proposal / insert_document | Save generated proposal to proposals | | list_recent_proposals | List latest saved proposals | | aggregate_documents | Project stats by industry |

Database collections

projects — seeded case studies (industry, description, outcome, budget)

proposals — saved generated proposals with requirements and timestamps

Seed the database

cd backend
.\.venv\Scripts\python seed_db.py

Test MCP tools locally

cd backend
.\.venv\Scripts\python scripts\test_mcp.py

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Agent test commands

Try these in the chat UI or ADK web UI:

Find logistics projects in the database

Show me the 3 most recent saved proposals

Save this proposal to MongoDB

Or paste a discovery call transcript and let the agent run the full pipeline.

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API endpoints

FastAPI (backend/main.py)

| Method | Path | Description | |--------|------|-------------| | POST | /proposal | Run 3-step Gemini pipeline (fallback) | | POST | /api/v1/proposal/generate | Same pipeline, versioned | | POST | /api/v1/proposal/save | Save proposal to MongoDB |

Next.js API routes

| Path | Description | |------|-------------| | /api/agent/chat | ADK session + auto-save | | /api/proposal | ADK or FastAPI proposal generation | | /api/anvil/pdf | Generate PDF from proposal text |

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Project structure

business-proposal-agent/
├── agent/
│   ├── dealpilot/
│   │   ├── agent.py          # Google ADK agent + MongoDB MCP
│   │   └── .env.example
│   ├── scripts/
│   │   └── start_agent.ps1
│   ├── system_prompt.md
│   └── mcp_setup.md
├── backend/
│   ├── main.py               # FastAPI API + fallback pipeline
│   ├── mcp_server.py         # MongoDB MCP server (FastMCP)
│   ├── seed_db.py            # Seed sample projects
│   └── scripts/test_mcp.py
├── frontend/
│   ├── app/
│   │   ├── api/agent/chat/   # ADK chat proxy
│   │   ├── api/anvil/pdf/    # PDF generation
│   │   └── page.tsx
│   └── components/
│       ├── AgentChat.tsx
│       └── ProposalOutput.tsx
└── README.md

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Hackathon compliance

| Requirement | Status | |-------------|--------| | Functional agent beyond chat | ✅ MongoDB tools + multi-step pipeline | | Multi-step mission | ✅ Analyze → Research → Generate | | MongoDB MCP integration | ✅ Custom MCP server on Atlas | | Google ADK / Agent Builder | ✅ ADK agent (dealpilot) | | Gemini powered | ✅ gemini-2.5-flash | | Open-source license | ✅ Add LICENSE file | | Public hosted URL | ⬜ Deploy to Vercel + Cloud Run | | Demo video (~3 min) | ⬜ Record and upload | | Devpost submission | ⬜ Complete form |

Track: MongoDB Partner Track — Google Cloud Rapid Agent Hackathon

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Troubleshooting

Agent not connecting to MongoDB

• Verify MONGODB_URI in backend/.env and agent/dealpilot/.env
• Run seed_db.py and scripts/test_mcp.py
• Restart the ADK agent after .env changes

Gemini 429 quota errors

• Free tier has daily limits; wait or use a new API key
• Enable the Gemini API in your Google Cloud project

PDF generation fails

• Set ANVIL_API_KEY in frontend/.env.local
• Restart the Next.js dev server after env changes

Official mongodb-mcp-server (npx) fails

• This project uses a custom FastMCP wrapper (backend/mcp_server.py) as a workaround
• See agent/mcp_setup.md for Agent Builder MCP configuration

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Team

Built for the Google Cloud Rapid Agent Hackathon (MongoDB Partner Track).

Repository: github.com/AaronTide/business-proposal-agent

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: AaronTide
• Source: AaronTide/business-proposal-agent
• License: MIT

Install and usage instructions live in the source repository linked above.