Hermes Agent
Open-source artificial intelligence agent developed by Nous Research
From Wikipedia, the free encyclopedia
Hermes Agent is an open-source artificial intelligence agent developed by Nous Research. It is designed to perform autonomous and multi-step tasks using large language models. Hermes Agent can be configured to use both locally hosted and remotely hosted LLMs.[4][5]
TypeScript[2]
| Hermes Agent | |
|---|---|
 | |
| Developer | Nous Research[1] |
| Release | February 2026 |
| Written in | Python TypeScript[2] |
| Operating system | Linux, macOS, Windows[3] |
| Type | Artificial intelligence agent |
| License | MIT License |
| Website | hermes-agent |
| Repository | github |
Capabilities
Hermes Agent can perform multi-step tasks by combining large language models with external tools and local resources. Its capabilities include tool calling, persistent memory, file system interaction, skill building, browser automation, messaging integrations and support for both cloud-based AI model providers[6] and locally hosted LLMs.[7][8]
Hermes Agent can be used through a command-line interface or as a native desktop application that runs locally on a user's computer.[9][10] Hermes Agent can connect to OpenRouter through an API key, allowing users to run the agent with models from multiple providers through a single interface.[11]
Deployment considerations
Advantages
- Organizations can run Hermes Agent on their own infrastructure, reducing the need to send proprietary source code, documents or other confidential data to third-party AI service providers.[12]
- Hermes Agent supports cloud-based model providers and locally hosted large language models, allowing deployments to be configured according to factors such as privacy, performance and operating cost.[13]
- As open-source software released under the MIT License,[14] Hermes Agent can be inspected, modified and extended for custom workflows and integrations.
Limitations
- Running Hermes Agent with locally hosted large language models generally requires suitable computing hardware, including sufficient processing power, memory, and storage.[15]
- Self-hosted deployments require organizations to install, configure, maintain and update both Hermes Agent and the underlying language models.[16]
- The capabilities and performance of Hermes Agent depend partly on the language model and computing hardware with which it is configured.[7]