MetaGPT

Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

MetaGPT: Collaborative AI for Complex Tasks

MetaGPT is a groundbreaking AI technology, designed to transform the landscape of software development. This innovative AI model can be thought of as a collaborative software entity, bringing together different roles within a software company to streamline complex tasks.

General
Relese date	August, 2023
Repository	https://github.com/geekan/MetaGPT
Type	Collaborative AI Agent

Start Building with MetaGPT

If you're ready to harness the power of MetaGPT for your software development projects, dive right in and start building!

MetaGPT Tutorials

MetaGPT Libraries

MetaGPT Documentation

Learn More About MetaGPT

Installation Guide: Get MetaGPT up and running quickly with step-by-step instructions.

Installation Guide: Get MetaGPT up and running quickly with step-by-step instructions.
MetaGPT's Abilities: Explore the full range of capabilities MetaGPT offers.
MetaGPT Quickstart: Dive into a quickstart guide to kickstart your projects with MetaGPT.
Product Demo: See MetaGPT in action with a product demo.
MetaGPT Discord Community: Join the MetaGPT community on Discord to connect with other users and developers.
MetaGPT Research Paper: Read the research paper to understand the technical details behind MetaGPT's capabilities.

MetaGPT is the future of software development, bringing unprecedented efficiency and innovation to your projects.

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MetaGPT AI technology page Hackathon projects

Discover innovative solutions crafted with MetaGPT AI technology page, developed by our community members during our engaging hackathons.

MediConnect: AI Emergency Response Platform

MediConnect is an AI-powered emergency response platform designed to provide rapid healthcare assistance during medical emergencies and disaster situations. The platform combines intelligent AI assistance with a hybrid token-efficient routing architecture to deliver accurate responses while minimizing cloud inference costs. Users can quickly access first-aid guidance, nearby hospital recommendations, emergency contacts, and disaster-related information through a simple interface. The system analyzes every incoming request and determines whether it can be handled locally or requires advanced cloud-based reasoning. Routine tasks such as first-aid instructions, emergency numbers, and basic healthcare guidance are processed locally to reduce latency and avoid unnecessary token consumption. More complex medical reasoning and disaster-response queries are securely routed to cloud AI models, ensuring high-quality answers while keeping resource usage efficient. MediConnect aims to improve emergency response by reducing waiting time, lowering operational costs, and making reliable healthcare information easily accessible. The platform is designed to support disaster management scenarios such as floods, earthquakes, fires, road accidents, and other emergencies where quick decision-making is critical. The project is built using modern AI technologies with a scalable architecture suitable for cloud deployment. Future enhancements include live ambulance tracking, multilingual assistance, GPS-based emergency routing, wearable device integration, predictive disaster alerts, and collaboration with healthcare organizations. MediConnect demonstrates how intelligent AI routing and emergency healthcare services can be combined to build a practical, scalable, and impactful solution for real-world emergencies.

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InnerOS: Sovereign Multi-Agent IT Field Swarm

InnerOS is a sovereign enterprise multi-agent swarm designed to automate critical IT field operations and diagnostic reporting, maximizing local data privacy. Operating within the Band network layer as its collaborative communication bus, the system registers 4 specialized external agents: Router, Memory Retrieval, Analyst, and Document Maker. When an operational query is received, the Router intercepts the request and handles internal orchestration via open-source LLMs hosted serverless on Featherless AI. The Memory Retrieval agent then queries a local MongoDB MCP enterprise database to unearth historical context and technical logs without leaking raw corporate information to the internet. Next, the Technical Analyst ingests this retrieved context, using advanced reasoning models via AIML API (DeepSeek-R1) to run root-cause diagnostics and evaluate infrastructure failures. Finally, the Document Maker synthesizes the analytical insights into an enterprise-grade, production-ready Executive Summary and SOP in English, automatically triggering a live webhook notification that dispatches the finalized report directly to the administrator's WhatsApp via Evolution API. By combining decentralized network coordination with a hybrid local-inference pipeline, InnerOS proves that enterprise automation can be fast, cost-effective, compliant, and strictly sovereign. Online Link: https://sworn-profusely-alongside.ngrok-free.dev/

BunoBagera AI

I built Bunobagera AI because I wanted to bridge the gap between writing code and shipping production-ready software. This isn't just a hackathon prototype—it is a robust, production-grade application engineered for real-world reliability. The frontend is built on Next.js for a lightning-fast, seamless UI, while the backend leverages Strapi as a powerful, flexible headless CMS. For data storage, I integrated Supabase to handle database management reliably at scale. At its core, the application uses the Mistral LLM to effectively analyze codebases for security, efficiency, and relevance. When you connect a repository, Bunobagera scans your code and enters an interactive chat interface to discuss fixes. The best part is the automation: if you approve the suggestions, it automatically creates a new branch and opens a Pull Request with the fixes. Beyond the code, it reviews your GitHub profile, providing a strategic summary and a personalized roadmap to help you grow your developer brand and stand out to recruiters.