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pentagi

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Fully autonomous AI Agents system capable of performing complex penetration testing tasks

Subagents15.9k stars2.2k forksGoMITUpdated today
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  • Actively maintained (<30d)
  • Healthy fork ratio
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  • Mature repo (>1y old)
Last scanned: 4/14/2026
Install in Claude Desktop
Method detected: Manual
{
  "mcpServers": {
    "pentagi": {
      "command": "node",
      "args": ["/path/to/pentagi/dist/index.js"]
    }
  }
}
1. Copy the snippet above.
2. Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows).
3. Replace any <placeholder> values with your API keys or paths.
4. Restart Claude Desktop. The MCP server appears automatically.
💡 Clone https://github.com/vxcontrol/pentagi and follow its README for install instructions.
Use cases

Subagents overview

# PentAGI

<div align="center" style="font-size: 1.5em; margin: 20px 0;">
    <strong>P</strong>enetration testing <strong>A</strong>rtificial <strong>G</strong>eneral <strong>I</strong>ntelligence
</div>
<br>
<div align="center">

> **Join the Community!** Connect with security researchers, AI enthusiasts, and fellow ethical hackers. Get support, share insights, and stay updated with the latest PentAGI developments.

[![Discord](https://img.shields.io/badge/Discord-7289DA?logo=discord&logoColor=white)](https://discord.gg/2xrMh7qX6m)⠀[![Telegram](https://img.shields.io/badge/Telegram-2CA5E0?logo=telegram&logoColor=white)](https://t.me/+Ka9i6CNwe71hMWQy)

<a href="https://trendshift.io/repositories/15161" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15161" alt="vxcontrol%2Fpentagi | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>

</div>

## Table of Contents

- [Overview](#overview)
- [Features](#features)
- [Architecture](#architecture)
  - [Agent Supervision](#advanced-agent-supervision)
- [Quick Start](#quick-start)
- [API Access](#api-access)
  - [LLM Provider Configuration](#custom-llm-provider-configuration)
    - [Ollama](#ollama-provider-configuration)
    - [OpenAI](#openai-provider-configuration)
    - [Anthropic](#anthropic-provider-configuration)
    - [Google AI (Gemini)](#google-ai-gemini-provider-configuration)
    - [AWS Bedrock](#aws-bedrock-provider-configuration)
    - [DeepSeek](#deepseek-provider-configuration)
    - [GLM](#glm-provider-configuration)
    - [Kimi](#kimi-provider-configuration)
    - [Qwen](#qwen-provider-configuration)
- [Advanced Setup](#advanced-setup)
  - [Langfuse Integration](#langfuse-integration)
  - [Monitoring and Observability](#monitoring-and-observability)
  - [Knowledge Graph (Graphiti)](#knowledge-graph-integration-graphiti)
  - [OAuth Integration](#github-and-google-oauth-integration)
  - [Docker Image Configuration](#docker-image-configuration)
- [Development](#development)
- [Testing LLM Agents](#testing-llm-agents)
- [Embedding Configuration and Testing](#embedding-configuration-and-testing)
- [Function Testing with ftester](#function-testing-with-ftester)
- [Building](#building)
- [Credits](#credits)
- [License](#license)

## Overview

PentAGI is an innovative tool for automated security testing that leverages cutting-edge artificial intelligence technologies. The project is designed for information security professionals, researchers, and enthusiasts who need a powerful and flexible solution for conducting penetration tests.

You can watch the video **PentAGI overview**:
[![PentAGI Overview Video](https://github.com/user-attachments/assets/0828dc3e-15f1-4a1d-858e-9696a146e478)](https://youtu.be/R70x5Ddzs1o)

## Features

- Secure & Isolated. All operations are performed in a sandboxed Docker environment with complete isolation.
- Fully Autonomous. AI-powered agent that automatically determines and executes penetration testing steps with optional execution monitoring and intelligent task planning for enhanced reliability.
- Professional Pentesting Tools. Built-in suite of 20+ professional security tools including nmap, metasploit, sqlmap, and more.
- Smart Memory System. Long-term storage of research results and successful approaches for future use.
- Knowledge Graph Integration. Graphiti-powered knowledge graph using Neo4j for semantic relationship tracking and advanced context understanding.
- Web Intelligence. Built-in browser via [scraper](https://hub.docker.com/r/vxcontrol/scraper) for gathering latest information from web sources.
- External Search Systems. Integration with advanced search APIs including [Tavily](https://tavily.com), [Traversaal](https://traversaal.ai), [Perplexity](https://www.perplexity.ai), [DuckDuckGo](https://duckduckgo.com/), [Google Custom Search](https://programmablesearchengine.google.com/), [Sploitus Search](https://sploitus.com) and [Searxng](https://searxng.org) for comprehensive information gathering.
- Team of Specialists. Delegation system with specialized AI agents for research, development, and infrastructure tasks, enhanced with optional execution monitoring and intelligent task planning for optimal performance with smaller models.
- Comprehensive Monitoring. Detailed logging and integration with Grafana/Prometheus for real-time system observation.
- Detailed Reporting. Generation of thorough vulnerability reports with exploitation guides.
- Smart Container Management. Automatic Docker image selection based on specific task requirements.
- Modern Interface. Clean and intuitive web UI for system management and monitoring.
- Comprehensive APIs. Full-featured REST and GraphQL APIs with Bearer token authentication for automation and integration.
- Persistent Storage. All commands and outputs are stored in PostgreSQL with [pgvector](https://hub.docker.com/r/vxcontrol/pgvector) extension.
- Scalable Architecture. Microservices-based design supporting horizontal scaling.
- Self-Hosted Solution. Complete control over your deployment and data.
- Flexible Authentication. Support for 10+ LLM providers ([OpenAI](https://platform.openai.com/), [Anthropic](https://www.anthropic.com/), [Google AI/Gemini](https://ai.google.dev/), [AWS Bedrock](https://aws.amazon.com/bedrock/), [Ollama](https://ollama.com/), [DeepSeek](https://www.deepseek.com/en/), [GLM](https://z.ai/), [Kimi](https://platform.moonshot.ai/), [Qwen](https://www.alibabacloud.com/en/), Custom) plus aggregators ([OpenRouter](https://openrouter.ai/), [DeepInfra](https://deepinfra.com/)). For production local deployments, see our [vLLM + Qwen3.5-27B-FP8 guide](examples/guides/vllm-qwen35-27b-fp8.md).
- API Token Authentication. Secure Bearer token system for programmatic access to REST and GraphQL APIs.
- Quick Deployment. Easy setup through [Docker Compose](https://docs.docker.com/compose/) with comprehensive environment configuration.

## Architecture

### System Context

```mermaid
flowchart TB
    classDef person fill:#08427B,stroke:#073B6F,color:#fff
    classDef system fill:#1168BD,stroke:#0B4884,color:#fff
    classDef external fill:#666666,stroke:#0B4884,color:#fff

    pentester["👤 Security Engineer
    (User of the system)"]

    pentagi["✨ PentAGI
    (Autonomous penetration testing system)"]

    target["🎯 target-system
    (System under test)"]
    llm["🧠 llm-provider
    (OpenAI/Anthropic/Ollama/Bedrock/Gemini/Custom)"]
    search["🔍 search-systems
    (Google/DuckDuckGo/Tavily/Traversaal/Perplexity/Sploitus/Searxng)"]
    langfuse["📊 langfuse-ui
    (LLM Observability Dashboard)"]
    grafana["📈 grafana
    (System Monitoring Dashboard)"]

    pentester --> |Uses HTTPS| pentagi
    pentester --> |Monitors AI HTTPS| langfuse
    pentester --> |Monitors System HTTPS| grafana
    pentagi --> |Tests Various protocols| target
    pentagi --> |Queries HTTPS| llm
    pentagi --> |Searches HTTPS| search
    pentagi --> |Reports HTTPS| langfuse
    pentagi --> |Reports HTTPS| grafana

    class pentester person
    class pentagi system
    class target,llm,search,langfuse,grafana external

    linkStyle default stroke:#ffffff,color:#ffffff
```

<details>
<summary><b>Container Architecture</b> (click to expand)</summary>

```mermaid
graph TB
    subgraph Core Services
        UI[Frontend UI<br/>React + TypeScript]
        API[Backend API<br/>Go + GraphQL]
        DB[(Vector Store<br/>PostgreSQL + pgvector)]
        MQ[Task Queue<br/>Async Processing]
        Agent[AI Agents<br/>Multi-Agent System]
    end

    subgraph Knowledge Graph
        Graphiti[Graphiti<br/>Knowledge Graph API]
        Neo4j[(Neo4j<br/>Graph Database)]
    end

    subgraph Monitoring
        Grafana[Grafana<br/>Dashboards]
        VictoriaMetrics[VictoriaMetrics<br/>Time-series DB]
        Jaeger[Jaeger<br/>Distributed Tracing]
        Loki[Loki<br/>Log Aggregation]
        OTEL[OpenTelemetry<br/>Data Collection]
    end

    subgraph Analytics
        Langfuse[Langfuse<br/>LLM Analytics]
        ClickHouse[ClickHouse<br/>Analytics DB]
        Redis[Redis<br/>Cache + Rate Limiter]
        MinIO[MinIO<br/>S3 Storage]
    end

    subgraph Security Tools
        Scraper[Web Scraper<br/>Isolated Browser]
        PenTest[Security Tools<br/>20+ Pro Tools<br/>Sandboxed Execution]
    end

    UI --> |HTTP/WS| API
    API --> |SQL| DB
    API --> |Events| MQ
    MQ --> |Tasks| Agent
    Agent --> |Commands| PenTest
    Agent --> |Queries| DB
    Agent --> |Knowledge| Graphiti
    Graphiti --> |Graph| Neo4j

    API --> |Telemetry| OTEL
    OTEL --> |Metrics| VictoriaMetrics
    OTEL --> |Traces| Jaeger
    OTEL --> |Logs| Loki

    Grafana --> |Query| VictoriaMetrics
    Grafana --> |Query| Jaeger
    Grafana --> |Query| Loki

    API --> |Analytics| Langfuse
    Langfuse --> |Store| ClickHouse
    Langfuse --> |Cache| Redis
    Langfuse --> |Files| MinIO

    classDef core fill:#f9f,stroke:#333,stroke-width:2px,color:#000
    classDef knowledge fill:#ffa,stroke:#333,stroke-width:2px,color:#000
    classDef monitoring fill:#bbf,stroke:#333,stroke-width:2px,color:#000
    classDef analytics fill:#bfb,stroke:#333,stroke-width:2px,color:#000
    classDef tools fill:#fbb,stroke:#333,stroke-width:2px,color:#000

    class UI,API,DB,MQ,Agent core
    class Graphiti,Neo4j knowledge
    class Grafana,VictoriaMetrics,Jaeger,Loki,OTEL monitoring
    class Langfuse,ClickHouse,Redis,MinIO analytics
    class Scraper,PenTest tools
```

</details>

<details>
<summary><b>Entity Relationship</b> (click to expand)</summary>

```mermaid
erDiagram
    Flow ||--o{ Task : contains
    Task ||--o{ SubTask : contains
    SubTask ||--o{ Action : contains
    Action ||--o{ Artifact : produces
    Action ||--o{ Memory : stores

    Flow {
        string id PK
        string name "Flow name"
        string description "Flow description"
        string status "active/completed/failed"
        json parameters "Flow parameters"
        timestamp created_at
       
ai-agentsai-security-toolanthropicautonomous-agentsgolanggptgraphqlmulti-agent-systemoffensive-securityopen-sourceopenaipenetration-testingpenetration-testing-toolsreactsecurity-automationsecurity-testingsecurity-toolsself-hosted

What people ask about pentagi

What is vxcontrol/pentagi?

+

vxcontrol/pentagi is subagents for the Claude AI ecosystem. Fully autonomous AI Agents system capable of performing complex penetration testing tasks It has 15.9k GitHub stars and was last updated today.

How do I install pentagi?

+

You can install pentagi by cloning the repository (https://github.com/vxcontrol/pentagi) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is vxcontrol/pentagi safe to use?

+

Our security agent has analyzed vxcontrol/pentagi and assigned a Trust Score of 100/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains vxcontrol/pentagi?

+

vxcontrol/pentagi is maintained by vxcontrol. The last recorded GitHub activity is from today, with 34 open issues.

Are there alternatives to pentagi?

+

Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.

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