agntz
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View .mdOptimized for LLMs — paste directly into ChatGPT, Claude, or Cursor.

Introduction

agntz is an open-source agent framework where agents are declared as YAML — not code — and run in three places: embedded in your app (@agntz/sdk for TypeScript, agntz for Python), on the hosted cloud (agntz.co), or on infrastructure you control (self-host). Manifests version prompts, models, schemas, tools, media operations, and retention policy independently from application code.

These docs are optimized for both humans and LLMs. Every page is also available as raw markdown — see the Copy button at the top of each page, or fetch /llms.txt for the full corpus.

What you can build

  • Single-call agents — an LLM with an instruction, optional tools, optional structured output.
  • Provider-replacement APIs — move direct text, multimodal, transcription, and image calls behind one versioned client contract.
  • Pipelines — sequential and parallel agents that compose other agents into multi-step workflows with loops and conditionals.
  • Tool agents — deterministic function calls with no LLM in the loop.
  • Long-running conversations — sessions persist message history across calls.
  • Streaming UIs — full event stream (tokens, tool calls, replies) over Server-Sent Events.
  • Managed media — upload image/audio inputs and receive expiring artifact references for generated files.
  • Multi-tenant products — every record is user-scoped on the hosted edition.

Three things stay the same as you scale from your laptop to production:

  1. The YAML schema. One manifest.yaml runs in embedded mode, hosted mode, and self-hosted mode.
  2. The client API. client.agents.run(...) — the same resource shape in TypeScript and Python, with language-native argument names.
  3. The result model. Output, provider/model identity, usage, warnings, resolved version, and retention metadata use the same normalized shape.

Choose your starting point

If you want to…UseRead
Run an agent on your laptop in 60 seconds@agntz/sdk or agntzQuickstart
Build agents from the terminalagntz CLICLI getting started
Author and run agents in a hosted UIagntz.coHosted cloud
Call hosted agents from your backend@agntz/client or AgntzClientHosted client
Replace direct provider API callsHosted or self-hosted workerProvider replacement
Deploy your own hosted stackDocker / Vercel + RailwaySelf-host

Install

# Embedded: run agents in-process from YAML files
pnpm add @agntz/sdk

# Hosted client: call agents on agntz.co or your own worker
pnpm add @agntz/client

# Optional persistence for embedded mode
pnpm add @agntz/stores

# CLI (run via npx or install globally)
npm i -g @agntz/sdk

Node 22+ for TypeScript. Python 3.11+ for Python. @agntz/client is universal across browser, Node, and edge runtimes; embedded SDKs read YAML from disk and run in your process.

Set the provider API key your agents will use:

export OPENAI_API_KEY=sk-...
# or ANTHROPIC_API_KEY=sk-ant-...
# or GOOGLE_GENERATIVE_AI_API_KEY=...
# or OPENROUTER_API_KEY=sk-or-...   # 300+ models incl. open-source via one key

Embedded runtimes call providers directly from your process. Hosted and self-hosted clients send run inputs to an Agntz worker, which owns the provider credentials and makes the configured model call. OpenRouter is available as a meta-provider when you want access to many models (Anthropic, Google, Meta, DeepSeek, open-source) with a single key — use provider: openrouter and a slug like anthropic/claude-sonnet-4 or meta-llama/llama-3.3-70b-instruct.

Where to go next

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