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mini-swe-agent

mini-swe-agent

Open Source(MIT)
Verified

The 100-line AI agent that solves GitHub issues or helps you in your command line.

Global
Self-hostable
Function calling
Public API
Free Forever
+2
Autonomous
Last updated: Oct 6, 2026
Open Source
Visit Site8.2k
More
mini-swe-agent.com

Quick Answer

AI

mini-SWE-agent is an open-source AI agent for developers and researchers that solves GitHub issues and assists with command-line tasks. It scores >74% on the SWE-bench verified benchmark and supports all models via LiteLLM, OpenRouter, and Portkey. Best for researchers and developers who need a minimal, hackable, and performant coding agent. Free and open-source.

About mini-swe-agentAI

mini-SWE-agent is an open-source AI agent designed for solving GitHub issues and assisting with command-line tasks. It features a minimal Python codebase, high performance on SWE-bench, and supports various local and containerized environments. The agent is free and open-source, focusing on simplicity and hackability for developers and researchers.

AI-extracted from public sources. May contain errors. Methodology · Report an error
What Makes mini-swe-agent UniqueAI

mini-SWE-agent is radically simpler than other agents, using only bash as a tool and maintaining a completely linear history for debugging and fine-tuning. It executes actions with independent subprocesses, making it highly stable and scalable for sandboxed environments.

Decision Intelligence

Best For

AI
Researchers building minimal AI agents and baselines
Developers seeking a simple, hackable command-line tool
Engineering teams doing fine-tuning or reinforcement learning on agents
Teams evaluating language models with SWE-bench
Pricing Overview

Type

Open Source

Starting Price

$0/mo

Free Trial

No

Credit Card

Not Required

Free Plan

Yes

Dimension Scores

· 5.0 avg

How good it is, across universal quality axes

Ease of Use1/10
Customization7/10
Support8/10
Integration4/10
Compliance & Data Protection5/10
Performance5/10
Planning Quality5/10
AI-analyzed from product data·High confidenceHow we score

Task Scores

· 5.1 avg

What it can do, per category it works in · showing 6 of 9 tasks scoring 5+

Bug Detection7/10
Context Understanding7/10
Refactoring6/10
Multi Language Support6/10
Code Explanation5/10
Test Generation5/10

Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →

Capabilities
Code
Automation
LimitationsAI
  • -Does not support custom tools beyond bash
  • -Does not have different history processors
Integrations & Connections
3 connections
LI
LitellmNative

Supports all models via LiteLLM

OP
OpenrouterNative

Supports all models via OpenRouter

PO
PortkeyNative

Supports all models via Portkey

Auto-updated

Fit Score

Complexity

Advanced

Company Size

Solo
Small
Medium
Enterprise

Team Size

Individual
Small Team
Large Team

Skill Level

Expert
Features
Minimal Python codebase (100 lines)
Scores >74% on SWE-bench verified benchmark
Supports local, Docker, Podman, Singularity, Apptainer, Bubblewrap, and Contree environments
Compatible with all models via LiteLLM, OpenRouter, and Portkey
Uses only bash as a tool, no complex tool-calling interfaces
Completely linear history for debugging and fine-tuning
Executes actions with independent subprocesses for stability and scalability
Python bindings for programmatic use
Technical Capabilities
SDK Available
MCP Compatible (unknown)
Multi-Agent (unknown)
Human-in-Loop
Team Features
Webhook Support (unknown)
Has Demo
Function Calling
Sandbox Mode (unknown)
Audit Logs
No Signup (unknown)
Works Offline (unknown)
Requires Host App
Framework
MCP Server

Deployment

Self Hosted
Developer Access
API
Public
HITL mode:
Approve
Compliance, Privacy & Trust
GDPR: No info available
SOC 2: No info available
HIPAA: No info available
Trains on user data: Unknown
Human review:
Recommended

The Model(s) Behind It

Model details — extracted from public vendor sources by our pipeline (Smart Generator + A3 cross-referencing) or admin-entered. Shown as claimed by the vendor; not independently audited by Intelloro.

Training Data Provenance
Not disclosed
Relevant to EU AI Act Art. 53 / Annex XI (GPAI)
Supported Tools
Bash Tool (Terminal)
Pricing Plans
Free
Free

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User Reviews

No reviews yet. Be the first to review!

Who It's For
4 roles
Software DevelopersComputer ProgrammersWeb Developers+1 more
Platform, Content & Languages
1 content types
1 languages
CodeEnglish+4 more

Output Languages

English

Content Types

Code

Accepts

Text
Code

Produces

Text
Code
Languages: English

Frequently Asked Questions

Trust Score

—

Insufficient data

Not enough verifiable data to score yet

Confidence: High

Reflects publicly available data, not an independent audit

Compliance & Verified38/38
VerifiedYes
Human ReviewYes
Human-in-the-loopYes
HITL TypeYes
Reliability0/10

No published data

Market Proof10/10
Notable CustomersMeta, NVIDIA, Essential AI
Company17/17
Company ListedYes
Health—

Not yet checked

AI-Assisted Data

Some details are AI-generated estimates — verify with the vendor.

AI-generated estimate: Best For, Description, Limitations, Quick Answer, Tagline, What Makes Unique

How we source data

AI Governance & Regulatory Disclosures

Legally-sensitive fields — extracted from public vendor sources by our pipeline (Smart Generator + A3 cross-referencing) or admin-entered. Shown as claimed by the vendor; not independently audited by Intelloro.

EU AI Act Risk Tier
Unclassified

Switching & Migration

Migration Difficulty
Easy to Switch
Support:
Slack
GitHub
Community
Quick Stats
Agent TypeAutonomous
MemoryShort Term
PlanningBasic
PlatformsCLI, API
VerifiedOct 2026
Company & Links

Company Name

Princeton University & Stanford University

Based in

United States

Last major update

Jan 2024

DocumentationChangelog