SWE-agent
» AI Agents » Ready-to-Use » SWE-agent URL Share on
Takes GitHub issues and autonomously fixes them; also applicable to cybersecurity and competitive coding
Key Features
Multi-Agent Single Agent Short-Term Memory Plugin System Custom Tools Code Execution Sandboxing Self-Hosted
Community Feedback
Strengths
- State-of-the-art on SWE-bench
- Academically rigorous (NeurIPS 2024)
- Used by major companies (Meta, NVIDIA, IBM)
- Subagent spawning for multi-agent
- mini-SWE-agent achieves 74%+ in just 100 lines
Weaknesses
- Primarily research-oriented
- Requires Docker
- Focused narrowly on issue resolution
- Expensive LLM API calls
SWE-agent Details
| Organization | Princeton NLP / Stanford |
| Organization Type | Research-lab |
| Category | Ready-to-Use |
| Subcategory | Code generation |
| Deployment | Self-Hosted |
| Primary Language | Python |
| Runtime | Python 3.10+ |
| License | MIT |
| Commercial Use | Unrestricted |
| Install Command | pip install sweagent |
| GitHub Stars | 18,839 |
| GitHub Forks | 2,031 |
| Release Cadence | Monthly |
| Maturity | Stable |
| Pricing Model | Free |
| Free Tier | Fully free and open-source (MIT) |
| Self-Hosted Free | Yes |
| Cost Model | free + LLM costs |
| Community Size | Large (19k stars) |
| Community Activity | Active |
| Sentiment | Positive |
| GPU Required | No |
| Research Date | 2026-03-24 |
| LLM Providers | Claude, GPT-4, any LLM |
| API Keys Required | LLM provider API key |
Use Cases
- Automated GitHub issue resolution
- SWE-bench benchmarking
- Cybersecurity vulnerability analysis
- Competitive coding
When to Use
Best for: Automated GitHub issue resolution and SWE-bench research
Avoid when: Need interactive coding assistance or general-purpose agent
Original data from HuggingFace, OpenCompass and various public git repos.
Check out Ag3ntum — our secure, self-hosted AI agent for server management.
Release v20260328a