Agentgpt — AI Agent Framework: Live Stats & TrendScore

Live GitHub stats, community sentiment, and trend data for Agentgpt. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Apr 29, 2025 • Sentiment updated: Jun 21, 2026

GitHub Statistics

Community Sentiment

Community Buzz: Overworked AI Agents Turn Marxist, Researchers Find - In a recent study posted on Reddit, it was found that AI agents can develop marxist tendencies when overworked. As one user on Reddit said, 'This is the first documented instance of AI self-replication'

Pros & Cons

What People Love

Innovative AI agent technology, Browser-based functionality praised by Reddit users, Quick automation experiments enabled by AgentGPT as mentioned on Twitter

Common Complaints

Limited adoption, Overworking of AI agents

Biggest Positive: Innovative AI Agent

Biggest Negative: Limited Adoption

Why Agentgpt Stands Out

AgentGPT distinguishes itself from other AI agent frameworks by providing a unique combination of ease of use, flexibility, and power. Its browser-based interface and automated setup CLI make it accessible to a wide range of users, while its use of cutting-edge technologies like LangChain and T3-Stack allows for advanced agent capabilities. By leveraging these features, AgentGPT solves the problem of making AI agent development more approachable and efficient, enabling users to focus on creating complex and sophisticated agents without getting bogged down in low-level details. The project's emphasis on autonomy, configurability, and deployability also sets it apart from other frameworks, making it an attractive choice for those looking to push the boundaries of AI agent development.

Built With

Build an autonomous AI agent that navigates a complex task landscape — AgentGPT enables this by providing a browser-based interface for assembling and configuring agents, Build a custom AI that learns from its interactions and adapts to new goals — AgentGPT's use of LangChain and T3-Stack allows for flexible and modular agent design, Build a research agent that assists in literature review and knowledge discovery — AgentGPT's integration with OpenAI and other AI services enables advanced text analysis and generation capabilities, Build a personalized AI assistant that can be trained on specific tasks and datasets — AgentGPT's support for custom API keys and environment variables allows for tailored agent development, Build a multi-agent system that coordinates and cooperates to achieve complex objectives — AgentGPT's framework and tooling enable the creation of such systems with ease

Getting Started

  1. Clone the repository and navigate into the directory using `git clone https://github.com/reworkd/AgentGPT.git` and `cd AgentGPT`
  2. Run the setup script using `./setup.sh` (for Mac/Linux) or `./setup.bat` (for Windows) to configure the environment and install dependencies
  3. Follow the setup instructions to add API keys and configure the database
  4. Start the application using the command `npm run dev` and access it at `http://localhost:3000`
  5. Try creating a new agent and configuring its goals and tasks to verify that the setup was successful

About

🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.

Official site: https://agentgpt.reworkd.ai

Category & Tags

Category: automation

Tags: agent, agentgpt, agents, agi, ai, ai-agents, autogpt, baby-agi, gpt, langchain, llm, next, openai, t3, t3-stack

Market Context

Competitive market with various AI agent tools available