Madurai Manji

[punithsai18]

Convo2Commit: Turn Meeting Dialogues into Project Milestones

Sprints and hackathons run on meetings.

Convo2Commit: Turn Meeting Dialogues into Project Milestones is an MCP (Model Context Protocol) server that extends AI assistants — like Claude, Cursor, and any MCP-compatible client — with new, real-world capabilities. It is built and deployed on Nitrostack, the fastest way to build, deploy, and share MCP apps.

Table of Contents

• Overview
• What is MCP?
• Features
• Available Tools
• Getting Started
• Connect to an MCP Client
• Deploy Your Own MCP App
• Explore More MCP Apps
• FAQ
• Keywords
• License

Overview

📌 The Problem

During fast-paced sprints and hackathons, teams spend hours in planning meetings. They delegate work, identify risks, and coordinate deadlines. However, translating meeting discussions into actual project tasks is broken:

• Admin Overhead: Manual transcription and copying tasks into project boards takes hours.
• Forgotten Deadlines: Scheduled meetings and deliverable dates are easily lost.
• Unchecked Risks: Bottlenecks (e.g., "API module is delayed") are discussed but never logged, leading to missed launch dates.
• Lack of Tracking: Overdue deliverables are rarely identified until it is too late.

💡 The Solution

Convo2Commit turns passive meeting recordings and transcripts into an active, self-managing project workspace. By combining a Next.js real-time visual dashboard with a NitroStack Model Context Protocol (MCP) server, the system automatically:

1. Listens to meeting transcripts or voice.
2. Extracts tasks, meetings, blockers, and audits.
3. Automatically routes action items to 4 specialized agents.
4. Generates instant PDF summaries for team distribution.

🧠 AI Architecture: 2-Layer Multi-Model Setup

We utilize a 2-Layer Multi-Model AI Architecture to ensure flexibility, speed, and accuracy:

1. Layer 1: The Client-Side Orchestrator (e.g., Claude 3.5 / GPT-4o)
   • Role: Acts as the natural-language chat interface.
   • Why: In NitroStack Studio, the user can choose their preferred model. This layer focuses on understanding user commands, mapping them to the correct MCP tools, and presenting the results back in clean markdown.
2. Layer 2: The Backend Extraction Engine (Gemini 1.5 Pro)
   • Role: Handles heavy document extraction and structural JSON parsing.
   • Why: Integrated directly into the analyze_transcript tool. When a raw meeting transcript is uploaded, this high-context model analyzes the conversational dialogue, categorizes the sentences, maps ownership, computes ISO date strings, and writes structure to the SQLite database.
   • Resilience Fallback: Includes a local regex-based keyword parsing engine to protect the live demo from API quota limits.

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What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI assistants securely connect to external tools, data sources, and services. Instead of being limited to what it was trained on, an AI model can call MCP servers to fetch live data, run actions, and integrate with real systems.

This project is one such MCP server. Learn more about building and shipping MCP apps at nitrostack.ai.

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Quick Workflow Example

1. Upload / Paste Transcript: The team inputs a raw Google Meet dialogue block:

   Aksha: Hey team, we need to complete the database migration module by tomorrow. Punith: I will handle it. Also, let's schedule a final review meeting on July 28th at 10 AM. By the way, the marketing campaign is delayed because our designer is sick. Let's check progress on the UI design task to see if it's overdue.

2. Trigger analyze_transcript: The AI breaks down the dialogue:
   • "complete database migration" → Task created for Punith.
   • "schedule final review on July 28" → Google Calendar meeting booked.
   • "marketing is delayed" → High Risk logged.
   • "check progress on UI design" → UI design flagged as Overdue.
3. Export report: Call export_tasks_pdf to instantly compile all items into a styled PDF summary.

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📊 Sample Transcript Analysis Output

When you run the transcript analyzer, the response is structured as follows:

✅ Tasks Created

1. Database migration module — Owner: Team | Deadline: Tomorrow
2. Assign task to Punith — Owner: Aksha | Deadline: Tomorrow
3. Check progress on UI design task — Owner: Team | Deadline: End of hackathon
4. Reassign UI design task — Owner: Team | Deadline: Today
5. Export tasks to PDF report — Owner: Team | Deadline: End of hackathon

📅 Calendar Events Scheduled

1. Project Demo — July 28th, 3:00 PM - 4:00 PM (Google Calendar link generated)

⚠️ Risks Logged

1. Marketing campaign delayed (HIGH RISK) — Reason: Designer is sick.

📈 Progress Audits

1. UI design task — Status: ❌ OVERDUE (Suggested reassignment)

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Features

• 🔌 MCP-native — works with any MCP-compatible client (Claude Desktop, Cursor, and more)
• 📋 Task Agent — creates, assigns, and lists workflow tasks for developers, designers, and marketing roles
• 📅 Calendar Agent — schedules meetings and deadlines directly into Google Calendar (via Calendar API v3)
• ⚠️ Risk Agent — flags bottleneck dependencies, computes launch timeline delays, and provides paired-dev mitigations
• 📈 Progress Agent — audits tasks, flags overdue milestones, and alerts project managers
• 📝 Transcript Pipeline — uploads/pastes Google Meet transcript logs, splitting actions to all agents in one click
• 📄 PDF Export — compiles current tasks and team status updates into a clean, print-ready PDF summary report
• ⚡ Deployed on Nitrostack — reliable, hosted, and instantly shareable
• 🔐 Secure by design — secrets stay in environment variables, never in code

Available Tools

1. create_task — Assign work
   • Extracts task title, owner (person/role), and deadline from message.
2. list_tasks — View all project tasks
   • Shows all active/completed/overdue tasks from the local SQLite database in a Markdown table.
3. update_task_status — Mark tasks done
   • Updates a task's status to completed, overdue, or active.
4. create_calendar_event — Schedule meetings
   • Adds a meeting or deadline directly to Google Calendar and persists it locally.
5. list_calendar_events — View scheduled meetings
   • Lists all scheduled meetings, dates, and links.
6. analyze_risk — Flag blocked/delayed work
   • Logs dependencies, estimates launch delay (e.g. 3-5 days), and suggests pair-programming mitigations.
7. list_risks — View logged risks
   • Shows all identified active risk logs and blockers.
8. check_progress — Track task status
   • Audits tasks against deadlines and triggers progress warnings.
9. list_progress_logs — View progress history
   • Displays historical logs of all progress and overdue checks.
10. analyze_transcript — Parse meeting notes
    • Reads a Google Meet transcript and automatically parses and routes items to all respective agent databases (includes built-in rate-limit heuristic fallback).
11. export_tasks_pdf — Export project summary
    • Generates a styled PDF report of all project tasks and saves it directly to your workspace.

Getting Started

Prerequisites

• Node.js 18+
• SQLite3
• An MCP-compatible client (Claude Desktop, Cursor, etc.)

Installation

git clone https://github.com/your-username/convo2commit.git
cd convo2commit/haul-mcp
npm install

Configuration

Copy the example environment file in both haul-mcp and haul-frontend directories and add your keys:

cp .env.example .env

Set the following variables in the backend .env:

• GOOGLE_CLIENT_ID
• GOOGLE_CLIENT_SECRET
• GOOGLE_REDIRECT_URI
• GOOGLE_REFRESH_TOKEN
• GEMINI_API_KEY

Run

To run the MCP server:

npm run build
npm run start

To run the Next.js visual dashboard:

cd ../haul-frontend
npm run dev

Connect to an MCP Client

Add this server to your MCP client configuration (e.g., in Cursor Settings -> Features -> MCP or compatibility.json). A typical entry looks like:

{
  "mcpServers": {
    "convo2commit": {
      "command": "npm",
      "args": ["run", "start"],
      "cwd": "/path/to/convo2commit/haul-mcp"
    }
  }
}

Restart your client and the tools from this MCP server will be available to your AI assistant.

Deploy Your Own MCP App

Want to build and ship an MCP server like this one? Nitrostack lets you create, deploy, and host MCP apps in minutes — no infrastructure to manage.

👉 Start building: https://nitrostack.ai

Explore More MCP Apps

• 🌙 Discover and share MCP projects with the community on r/mcptothemoon
• 🧰 Browse a growing catalog of MCP apps on Nitrostack

FAQ

What is an MCP server?

An MCP server implements the Model Context Protocol to expose tools, resources, and prompts that AI assistants can call. It lets an AI model take real actions and access live data.

What does Convo2Commit do?

It parses conversational meeting dialogue, uploads transcripts, manages tasks, schedules meetings on Google Calendar, and logs risk audits automatically.

Which AI clients does this work with?

Any MCP-compatible client, including Claude Desktop, Cursor, and NitroStudio.

Keywords

Education & Research · Convo2Commit: Turn Meeting Dialogues into Project Milestones · MCP · Model Context Protocol · MCP server · MCP app · AI tools · AI agents · LLM tools · Claude MCP · Nitrostack · deploy MCP server · build MCP app

License

MIT © 2026

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Built with ❤️ using the Model Context Protocol on Nitrostack. Share your MCP app on r/mcptothemoon.