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Async Hermes Agent Documentation

Free

Async-first Hermes agent core for training, trajectories, tools, skills, MCP, and service integration

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At a glance

Explore the listed capabilities, then check the details that matter to you.

  • Embed agents in async Python applications
  • Run agent loops through coroutine APIs
  • Extend agents with reusable tools
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Async Hermes Agent Documentation screenshot 1

Overview

Async Hermes Agent is an async-only Python library derived from the upstream NousResearch/Hermes Agent, based on release v2026.8.18. It converts the Hermes Agent harness into coroutine entry points, retaining the upstream agent loop, tools, providers, MCP, skills, memory, sessions, trajectories, runner, and batch runner. The library supports Python 3.11 through 3.13 and is installable from PyPI. It maintains familiar module paths and public names, with I/O-bearing calls awaited, allowing the host application to own its HTTP service or UI while the agent remains a reusable harness.

The library provides an async library surface where model, tool, MCP, session, trajectory, runner, and batch-runner entry points are awaited under their upstream names. It includes extensible tool use with retained terminal, file, web, browser, vision, skills, memory, session-search, clarification, delegation, and plugin tools. MCP support enables dynamic stdio, Streamable HTTP, and SSE server discovery with ordered tool observations and explicit async lifecycle cleanup. Persistent context is managed through SQLite sessions, memory, user-profile context, FTS history search, checkpoints, and resume.

For training data, the library preserves reasoning, tool calls, observations, and final answers, and can generate JSONL trajectories with bounded batch concurrency. It is service-ready, allowing embedding in FastAPI or another async host without bundling a second service framework or HTTP contract. The implementation uses coroutine transports for provider, network, MCP, and subprocess paths, while regular-file operations use aiofiles and SQLite uses aiosqlite, promising directly awaitable, event-loop-nonblocking entry points.

Pricing

Free

Detailed plans have not been confirmed in our catalog. Check the official website for current limits and billing terms.

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Use Cases

  • Teams use Async Hermes Agent to embed an agent in FastAPI or another async host.
  • Teams use Async Hermes Agent to generate JSONL trajectories for training data.
  • Teams use Async Hermes Agent to maintain persistent context across sessions.
  • Teams use Async Hermes Agent to connect to MCP servers.
  • Teams use Async Hermes Agent to extend agent capabilities with tools.
  • Teams use Async Hermes Agent to provide reusable skill documents.

Features

Embed agents in async Python applications

Run agent loops through coroutine APIs

Extend agents with reusable tools

Connect to MCP servers dynamically

Persist sessions and memory in SQLite

Search prior session history

Resume agents from saved checkpoints

Generate JSONL agent trajectories

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