Open Source AI Agent Licenses: MIT, Apache, GPL

Why Licenses Matter for AI Agents

AI agent licenses carry more practical weight than licenses for typical libraries or tools because agents often become central infrastructure in your workflow. A coding agent that edits your source code, a support agent that handles customer conversations, or an automation agent that processes your business data becomes deeply embedded in your operations. Switching to a different agent later because of license issues is expensive and disruptive. Understanding the license implications before you build on a project prevents costly migrations.

Commercial use restrictions vary dramatically between licenses. Some licenses (MIT, Apache 2.0) impose virtually no restrictions on commercial use. Others (AGPL-3.0) require that you release the source code of any modifications if you provide the software as a service. Still others (Elastic License 2.0, Business Source License) explicitly restrict competing with the original vendors hosted offering. Choosing the wrong license for your use case can create legal liability or force you to open-source code you intended to keep proprietary.

Modification and distribution rules affect how you can customize and deploy agents. If you modify an agent to fit your specific workflow, some licenses require you to share those modifications publicly while others let you keep them proprietary. For organizations that invest engineering effort in customizing open source agents, this distinction determines whether your competitive advantage from customization is protectable.

Patent clauses differ between licenses and matter more than most developers realize. Apache 2.0 includes an explicit patent grant that protects you from patent claims by contributors. MIT does not include patent language. For enterprise deployments where patent risk is a concern, the Apache 2.0 patent grant provides meaningful legal protection that MIT does not offer.

MIT License

The MIT license is the most permissive common open source license. It allows commercial use, modification, distribution, and private use with no restrictions beyond including the original copyright notice. You can use MIT-licensed agents in proprietary products, modify them without sharing changes, and sell products built on them. The only obligation is preserving the copyright and license text.

Popular AI agents using MIT include Aider, Browser Use, GPT Researcher, Perplexica, Open WebUI, LibreChat, CrewAI, Stagehand, and Mem0. The prevalence of MIT in the AI agent ecosystem reflects the community preference for maximum adoption over contribution requirements.

MIT is the safest choice for commercial projects because it imposes the fewest obligations. If you are evaluating agents for a commercial product and want to minimize legal risk, prioritize MIT-licensed projects. The lack of patent language is the only notable limitation compared to Apache 2.0.

Apache 2.0 License

Apache 2.0 provides the same permissive commercial use rights as MIT but adds an explicit patent grant and a contribution clause. The patent grant means contributors cannot sue you for patent infringement related to their contributions. The contribution clause means any changes contributed back to the project are automatically licensed under Apache 2.0. These additions make Apache 2.0 more enterprise-friendly than MIT.

Popular AI agents using Apache 2.0 include Dify, Ontheia, Tabby, Cline, Continue.dev, Codex CLI, Hermes Agent, CAMEL, OWL, and Mastra. Enterprise-focused projects tend to prefer Apache 2.0 because its patent provisions satisfy legal department requirements that MIT does not address.

Choose Apache 2.0 licensed projects when patent protection matters to your organization. For most individual developers and small teams, the practical difference between MIT and Apache 2.0 is negligible. For enterprise deployments where legal review is standard, Apache 2.0 license often passes legal review faster because its patent clause eliminates a category of risk.

GPL and AGPL Licenses

GPL-3.0 requires that any distributed software that includes or links to GPL code must also be released under GPL. This means if you embed a GPL-licensed agent in your product and distribute it to users, your entire product must be GPL-licensed and the source code must be available. This is known as the copyleft or viral nature of GPL. For purely internal use (no distribution), GPL imposes no sharing requirements.

AGPL-3.0 extends GPL copyleft to network use. If you run AGPL-licensed software as a service (which is how most AI agents are deployed), you must release your source code including any modifications. This closes the SaaS loophole that allows companies to modify GPL software and offer it as a cloud service without sharing changes. Skyvern uses AGPL-3.0, which means running it as a hosted service triggers the source code sharing requirement.

For internal-only deployments where the agent never serves external users, both GPL and AGPL are functionally similar to permissive licenses because the sharing requirements only apply to distribution or network access by external users. If your agent runs on your internal network and only serves your employees, you can modify it freely without sharing changes. But verify this interpretation with your legal team because the boundaries of internal use can be complex.

The practical impact of AGPL for AI agents is significant because most agents are deployed as services rather than distributed as software. If you plan to offer a product that includes an AGPL-licensed component, you need to either release your product source code, negotiate a separate commercial license with the copyright holder, or choose a differently licensed alternative.

Non-Standard and Source-Available Licenses

Several popular AI tools use licenses that are not approved by the Open Source Initiative (OSI) and impose additional restrictions beyond traditional open source licenses. n8n uses a Sustainable Use License (sometimes called Fair Code) that allows self-hosting and modification but restricts competing with n8ns hosted offering. This means you can use n8n internally but cannot offer it as a hosted automation platform to your customers.

Elastic License 2.0 (used by Composio) allows most use cases but explicitly prohibits providing the software as a managed service that competes with the vendor. This restriction targets companies that would take the open source code and offer a competing hosted version without contributing back.

Business Source License (BSL) starts as a restrictive license that converts to an open source license (typically MIT or Apache 2.0) after a specified time period (usually 2-4 years). This gives the original vendor exclusive commercial rights during the initial period while guaranteeing eventual open source availability. Some AI agent projects use BSL to balance commercial sustainability with open source principles.

Evaluate non-standard licenses carefully because they may not meet the legal definitions of open source and may impose unexpected restrictions on your use case. Always have your legal team review non-OSI-approved licenses before building on projects that use them. The source code availability does not automatically mean you can use it however you want.

Choosing by License for Your Use Case

For commercial SaaS products, stick with MIT or Apache 2.0 licensed agents. These licenses impose minimal obligations and will not force you to open-source your proprietary code. Avoid AGPL-licensed components in any product you offer as a service unless you are willing to release your source code.

For internal enterprise tools, any license works because internal-only deployment typically does not trigger distribution or network service requirements. Even AGPL-licensed agents can be freely modified for internal use without sharing changes. Verify this with your legal team if your internal tool might be accessed by external parties such as contractors or partners.

For open source projects, consider reciprocal licenses (GPL, AGPL) if you want to ensure that improvements to your project are shared back with the community. Permissive licenses (MIT, Apache 2.0) maximize adoption but allow companies to take your code without contributing back. Choose based on whether you prioritize community contribution or maximum adoption.