\u201cHermes Agent is an autonomous AI agent framework available on GitHub under the MIT license. It was built by Nous Research and is positioned as a self-improving AI agent that learns from repeated use. \u201c <\/p>\n\n\n\n
The Hermes AI agent connects to model providers such as Nous Portal, OpenRouter, OpenAI and other OpenAI-compatible endpoints. This gives developers flexibility over which model powers the agent instead of forcing them into one provider. <\/p>\n\n\n\n
Where many AI tools are built around single sessions, Hermes Agent focuses on continuity. It can maintain memory across sessions, search past conversations, create reusable skills and improve those skills during use. That makes it useful for developers working on long-running projects, recurring workflows and self-hosted automation. <\/p>\n\n\n\n
Hermes Agent can run on Linux, macOS, WSL2 and self-hosted environments such as a VPS or Docker container. The official quickstart is designed to get users from installation to a working conversation quickly. <\/p>\n\n\n\n
To see why Hermes Agent matters, start with the limitations developers face with most AI assistants today. <\/p>\n\n\n\n
What problem does Hermes agent solve?<\/strong> <\/h2>\n\n\n\nMost AI tools are built for short sessions. They answer questions, complete tasks and then lose the working context when the session ends. Every time a developer returns, they may need to explain the project, repeat instructions and rebuild context that should already be available. <\/p>\n\n\n\n
Running agents only on a local machine can create more limitations. For developers managing long or complex workflows, four problems come up often: <\/p>\n\n\n\n
\n- Session reset:<\/strong> The agent may forget prior context when the conversation ends. <\/li>\n<\/ul>\n\n\n\n
\n- Local dependency:<\/strong> The agent stops when the laptop shuts down, which makes overnight tasks and background workflows harder. <\/li>\n<\/ul>\n\n\n\n
\n- Provider lock-in:<\/strong> Some agent setups are tied closely to one model provider, making it harder to switch endpoints or control cost. <\/li>\n<\/ul>\n\n\n\n
\n- No long-term project context:<\/strong> Larger projects need an agent that remembers decisions, past work and repeatable steps across days or weeks. <\/li>\n<\/ul>\n\n\n\n
Hermes Agent is built to address these problems through persistent memory, model flexibility, self-hosted deployment and skill creation. <\/p>\n\n\n\n
Once you understand the problem, the next step is to look at how Hermes Agent keeps tasks, tools and memory running together. <\/p>\n\n\n\n
How Hermes agent works?<\/strong> <\/h2>\n\n\n\nHermes Agent runs as a persistent service on self-hosted infrastructure. It receives input, sends the task to a configured language model<\/a>, executes tools, stores useful results in memory and repeats the loop until the task is complete. <\/p>\n\n\n\nA VPS is one practical option for running Hermes Agent 24\/7 because the agent can stay online even when your personal machine is closed. Docker can be useful when you want isolated execution. Local setup works well for testing, but it is less suitable for long-running background workflows. <\/p>\n\n\n\n![\"how-hermes-agent-work\"](\"https:\/\/www.bluehost.com\/blog\/wp-content\/uploads\/2026\/04\/how-hermes-agent-work-1024x576.png\")
<\/figure>\n\n\n\nStep 1: Receiving input<\/strong> <\/h3>\n\n\n\nA task reaches Hermes Agent through the CLI, a messaging platform, a scheduled workflow or another connected interface. Developers can start with the terminal and later connect platforms like Telegram, Discord or Slack depending on their setup. <\/p>\n\n\n\n
Step 2: Task planning with a language model<\/strong> <\/h3>\n\n\n\nHermes Agent sends the request to the configured model along with relevant context, memory and available tools. It supports OpenAI-compatible endpoints, which gives developers more control over model choice, cost and hosting setup. <\/p>\n\n\n\n
Step 3: Tool execution<\/strong> <\/h3>\n\n\n\nThe Hermes Agent AI framework can call tools for terminal work, file editing, browser tasks, code execution and connected integrations. Tool outputs are fed back into the agent loop so it can decide the next step. <\/p>\n\n\n\n
Step 4: Memory storage and retrieval<\/strong> <\/h3>\n\n\n\nHermes Agent stores useful context so future sessions can build on earlier work. This is one of its main differences from many AI assistants that are optimized for a single session or one coding workflow. <\/p>\n\n\n\n
Step 5: Continuous operation<\/strong> <\/h3>\n\n\n\nAfter a task is complete, Hermes Agent can wait for the next trigger instead of shutting down. This is why Hermes Agent hosting on a VPS makes sense for developers who want to run an AI agent 24\/7. <\/p>\n\n\n\n
Together, these steps create a persistent agent loop that can work across tasks, platforms and sessions. <\/p>\n\n\n\n
What features does Hermes agent give developers?<\/strong> <\/h2>\n\n\n\nHermes Agent is an open-source AI agent framework<\/a> built for developers who need more than a one-session assistant. Available on the Nous Research GitHub, every feature is designed around one idea: a self-hosted AI agent that runs continuously, learns from experience and works across the tools and platforms developers already use. <\/p>\n\n\n\n1. Multi-platform messaging support<\/strong> <\/h3>\n\n\n\nHermes Agent connects to Telegram, Discord, Slack, WhatsApp, Signal, Email and CLI from a single messaging gateway. Start a task on one platform and pick it up on another without losing context. <\/p>\n\n\n\n
2. Persistent memory and skill generation<\/strong> <\/h3>\n\n\n\nThe Hermes AI agent builds persistent memory across sessions and auto-generates reusable skills from experience. It learns your projects, retains how it solved problems before and gets more capable the longer it runs on self-hosted infrastructure. <\/p>\n\n\n\n
3. Scheduled automation and background tasks<\/strong> <\/h3>\n\n\n\nHermes Agent supports natural language cron scheduling<\/a> for reports, backups and briefings. Tasks run unattended through the gateway, making it a practical choice for developers who need to run an AI agent 24\/7 without manual input. <\/p>\n\n\n\n4. Subagent delegation and parallel execution<\/strong> <\/h3>\n\n\n\nHermes Agent can spawn isolated subagents with their own conversations, terminals and Python RPC scripts. This makes it possible to run parallel workstreams with zero context cost, useful for complex pipelines that would otherwise require multiple separate tools. <\/p>\n\n\n\n
5. Sandboxed execution environments<\/strong> <\/h3>\n\n\n\nHermes Agent supports five deployment backends: local, Docker, SSH, Singularity and Modal. Each environment includes container hardening with read-only root, dropped capabilities and namespace isolation, giving developers real security controls when hosting Hermes Agent on a VPS or remote server. <\/p>\n\n\n\n
6. Web and browser control<\/strong> <\/h3>\n\n\n\nHermes Agent includes built-in tools for web search, browser automation, vision, image generation, text-to-speech and multi-model reasoning. Developers can run full web workflows directly through the Hermes Agent AI framework without connecting third-party tools. <\/p>\n\n\n\n
What are the real-world use cases for Hermes agent?<\/strong> <\/h2>\n\n\n\nHermes Agent can support developers and researchers who need autonomous AI workflows that keep running beyond a single prompt. Here are the main use cases developers and researchers are running on the Nous Research Hermes Agent today. <\/p>\n\n\n\n
Interactive CLI coding assistant<\/strong> <\/h3>\n\n\n\nHermes Agent works as a terminal assistant for writing, reviewing and running code. Pass project files directly into the conversation using context files and the agent reads, edits and executes code in your projects without leaving the terminal. <\/p>\n\n\n\n
Telegram and Discord bot<\/strong> <\/h3>\n\n\n\nDeploy the Hermes AI agent as a bot on Telegram, Discord or any supported messaging platform. Common production setups include a daily briefing bot and a team Telegram assistant, both running unattended on self-hosted infrastructure. <\/p>\n\n\n\n
Scheduled automation and background tasks<\/strong> <\/h3>\n\n\n\nHermes Agent supports cron scheduling for daily summaries, periodic checks and automated reports, running without you being present. Batch processing and delegation let developers chain agent actions together and run parallel workstreams across longer workflows. <\/p>\n\n\n\n
Custom tools and skills<\/strong> <\/h3>\n\n\n\nExtend the hermes-agent with your own tools and reusable skill packages. Tools are individual functions the agent can call. Skills are bundles of tools, prompts and configuration packaged together. The open source codebase supports MCP integration for connecting external tool servers. <\/p>\n\n\n\n
Model training and RL pipelines<\/strong> <\/h3>\n\n\n\nUse the Hermes Agent AI framework to fine-tune model behavior with a built-in reinforcement learning training pipeline. Covers provider routing, batch trajectory generation and architecture-level configuration for developers building and evaluating models. <\/p>\n\n\n\n
Python library integration<\/strong> <\/h3>\n\n\n\nIntegrate the self-hosted Hermes Agent directly into Python applications programmatically. Covers sessions, tools, architecture and the full Python library guide for developers building on top of the agent. <\/p>\n\n\n\n
How does Hermes Agent compare with other AI agents?<\/strong> <\/h2>\n\n\n\nHermes Agent is not the only AI agent or automation tool developers can use. It overlaps with coding assistants, workflow automation platforms, no-code AI assistants and self-hosted AI agent tools. The right choice depends on whether you need long-term memory, VPS hosting<\/a>, app automation, coding support or multi-agent orchestration. <\/p>\n\n\n\nThe comparison below shows where Hermes Agent fits against OpenClaw, Paperclip, Lindy AI, n8n and Claude Code before breaking down each tool in more detail. <\/p>\n\n\n\n
Comparison table<\/strong> <\/h3>\n\n\n\nUse this table as a quick snapshot of how Hermes Agent compares with other AI agents across use case, self-hosting support, memory, automation style and VPS hosting fit. <\/p>\n\n\n\n
- \n
- Local dependency:<\/strong> The agent stops when the laptop shuts down, which makes overnight tasks and background workflows harder. <\/li>\n<\/ul>\n\n\n\n
- \n
- Provider lock-in:<\/strong> Some agent setups are tied closely to one model provider, making it harder to switch endpoints or control cost. <\/li>\n<\/ul>\n\n\n\n
- \n
- No long-term project context:<\/strong> Larger projects need an agent that remembers decisions, past work and repeatable steps across days or weeks. <\/li>\n<\/ul>\n\n\n\n
Hermes Agent is built to address these problems through persistent memory, model flexibility, self-hosted deployment and skill creation. <\/p>\n\n\n\n
Once you understand the problem, the next step is to look at how Hermes Agent keeps tasks, tools and memory running together. <\/p>\n\n\n\n
How Hermes agent works?<\/strong> <\/h2>\n\n\n\n
Hermes Agent runs as a persistent service on self-hosted infrastructure. It receives input, sends the task to a configured language model<\/a>, executes tools, stores useful results in memory and repeats the loop until the task is complete. <\/p>\n\n\n\n
A VPS is one practical option for running Hermes Agent 24\/7 because the agent can stay online even when your personal machine is closed. Docker can be useful when you want isolated execution. Local setup works well for testing, but it is less suitable for long-running background workflows. <\/p>\n\n\n\n
<\/figure>\n\n\n\nStep 1: Receiving input<\/strong> <\/h3>\n\n\n\n
A task reaches Hermes Agent through the CLI, a messaging platform, a scheduled workflow or another connected interface. Developers can start with the terminal and later connect platforms like Telegram, Discord or Slack depending on their setup. <\/p>\n\n\n\n
Step 2: Task planning with a language model<\/strong> <\/h3>\n\n\n\n
Hermes Agent sends the request to the configured model along with relevant context, memory and available tools. It supports OpenAI-compatible endpoints, which gives developers more control over model choice, cost and hosting setup. <\/p>\n\n\n\n
Step 3: Tool execution<\/strong> <\/h3>\n\n\n\n
The Hermes Agent AI framework can call tools for terminal work, file editing, browser tasks, code execution and connected integrations. Tool outputs are fed back into the agent loop so it can decide the next step. <\/p>\n\n\n\n
Step 4: Memory storage and retrieval<\/strong> <\/h3>\n\n\n\n
Hermes Agent stores useful context so future sessions can build on earlier work. This is one of its main differences from many AI assistants that are optimized for a single session or one coding workflow. <\/p>\n\n\n\n
Step 5: Continuous operation<\/strong> <\/h3>\n\n\n\n
After a task is complete, Hermes Agent can wait for the next trigger instead of shutting down. This is why Hermes Agent hosting on a VPS makes sense for developers who want to run an AI agent 24\/7. <\/p>\n\n\n\n
Together, these steps create a persistent agent loop that can work across tasks, platforms and sessions. <\/p>\n\n\n\n
What features does Hermes agent give developers?<\/strong> <\/h2>\n\n\n\n
Hermes Agent is an open-source AI agent framework<\/a> built for developers who need more than a one-session assistant. Available on the Nous Research GitHub, every feature is designed around one idea: a self-hosted AI agent that runs continuously, learns from experience and works across the tools and platforms developers already use. <\/p>\n\n\n\n
1. Multi-platform messaging support<\/strong> <\/h3>\n\n\n\n
Hermes Agent connects to Telegram, Discord, Slack, WhatsApp, Signal, Email and CLI from a single messaging gateway. Start a task on one platform and pick it up on another without losing context. <\/p>\n\n\n\n
2. Persistent memory and skill generation<\/strong> <\/h3>\n\n\n\n
The Hermes AI agent builds persistent memory across sessions and auto-generates reusable skills from experience. It learns your projects, retains how it solved problems before and gets more capable the longer it runs on self-hosted infrastructure. <\/p>\n\n\n\n
3. Scheduled automation and background tasks<\/strong> <\/h3>\n\n\n\n
Hermes Agent supports natural language cron scheduling<\/a> for reports, backups and briefings. Tasks run unattended through the gateway, making it a practical choice for developers who need to run an AI agent 24\/7 without manual input. <\/p>\n\n\n\n
4. Subagent delegation and parallel execution<\/strong> <\/h3>\n\n\n\n
Hermes Agent can spawn isolated subagents with their own conversations, terminals and Python RPC scripts. This makes it possible to run parallel workstreams with zero context cost, useful for complex pipelines that would otherwise require multiple separate tools. <\/p>\n\n\n\n
5. Sandboxed execution environments<\/strong> <\/h3>\n\n\n\n
Hermes Agent supports five deployment backends: local, Docker, SSH, Singularity and Modal. Each environment includes container hardening with read-only root, dropped capabilities and namespace isolation, giving developers real security controls when hosting Hermes Agent on a VPS or remote server. <\/p>\n\n\n\n
6. Web and browser control<\/strong> <\/h3>\n\n\n\n
Hermes Agent includes built-in tools for web search, browser automation, vision, image generation, text-to-speech and multi-model reasoning. Developers can run full web workflows directly through the Hermes Agent AI framework without connecting third-party tools. <\/p>\n\n\n\n
What are the real-world use cases for Hermes agent?<\/strong> <\/h2>\n\n\n\n
Hermes Agent can support developers and researchers who need autonomous AI workflows that keep running beyond a single prompt. Here are the main use cases developers and researchers are running on the Nous Research Hermes Agent today. <\/p>\n\n\n\n
Interactive CLI coding assistant<\/strong> <\/h3>\n\n\n\n
Hermes Agent works as a terminal assistant for writing, reviewing and running code. Pass project files directly into the conversation using context files and the agent reads, edits and executes code in your projects without leaving the terminal. <\/p>\n\n\n\n
Telegram and Discord bot<\/strong> <\/h3>\n\n\n\n
Deploy the Hermes AI agent as a bot on Telegram, Discord or any supported messaging platform. Common production setups include a daily briefing bot and a team Telegram assistant, both running unattended on self-hosted infrastructure. <\/p>\n\n\n\n
Scheduled automation and background tasks<\/strong> <\/h3>\n\n\n\n
Hermes Agent supports cron scheduling for daily summaries, periodic checks and automated reports, running without you being present. Batch processing and delegation let developers chain agent actions together and run parallel workstreams across longer workflows. <\/p>\n\n\n\n
Custom tools and skills<\/strong> <\/h3>\n\n\n\n
Extend the hermes-agent with your own tools and reusable skill packages. Tools are individual functions the agent can call. Skills are bundles of tools, prompts and configuration packaged together. The open source codebase supports MCP integration for connecting external tool servers. <\/p>\n\n\n\n
Model training and RL pipelines<\/strong> <\/h3>\n\n\n\n
Use the Hermes Agent AI framework to fine-tune model behavior with a built-in reinforcement learning training pipeline. Covers provider routing, batch trajectory generation and architecture-level configuration for developers building and evaluating models. <\/p>\n\n\n\n
Python library integration<\/strong> <\/h3>\n\n\n\n
Integrate the self-hosted Hermes Agent directly into Python applications programmatically. Covers sessions, tools, architecture and the full Python library guide for developers building on top of the agent. <\/p>\n\n\n\n
How does Hermes Agent compare with other AI agents?<\/strong> <\/h2>\n\n\n\n
Hermes Agent is not the only AI agent or automation tool developers can use. It overlaps with coding assistants, workflow automation platforms, no-code AI assistants and self-hosted AI agent tools. The right choice depends on whether you need long-term memory, VPS hosting<\/a>, app automation, coding support or multi-agent orchestration. <\/p>\n\n\n\n
The comparison below shows where Hermes Agent fits against OpenClaw, Paperclip, Lindy AI, n8n and Claude Code before breaking down each tool in more detail. <\/p>\n\n\n\n
Comparison table<\/strong> <\/h3>\n\n\n\n
Use this table as a quick snapshot of how Hermes Agent compares with other AI agents across use case, self-hosting support, memory, automation style and VPS hosting fit. <\/p>\n\n\n\n
- No long-term project context:<\/strong> Larger projects need an agent that remembers decisions, past work and repeatable steps across days or weeks. <\/li>\n<\/ul>\n\n\n\n
- Provider lock-in:<\/strong> Some agent setups are tied closely to one model provider, making it harder to switch endpoints or control cost. <\/li>\n<\/ul>\n\n\n\n