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NanoClaw and OpenClaw are lightweight Python agent runners. They don’t bundle credential management. Authsome fills that gap. The same patterns work for any Python-native agent runner. For Hermes Agent, use the dedicated Hermes Agent page. Its primary integration is the agentskills.io skill install path, not the patterns below.

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Run under the proxy

authsome login github
authsome login openai
authsome run -- python -m <your_runner>
The runner sees placeholder env vars. Outbound HTTPS to matched providers is authenticated at the proxy layer. This is the recommended path.

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Export when the proxy is not enough

If you need explicit env vars in the runner process: 
eval "$(authsome export github --format env)"
eval "$(authsome export openai --format env)"
python -m <your_runner>
See Python library for the daemon HTTP API.

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When to use which

Use the proxyUse export
You want a single layer that catches every outbound call.You need fine-grained control over which connection to use per agent.
You’re using third-party clients you can’t easily modify.The agent is yours and reads env vars directly.
You need transparent injection for shell tools the agent spawns.You don’t spawn shell tools.

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What’s next

Run agents with the proxy

The proxy injection model.

Python library

the CLI export path or the daemon HTTP API.