Practical overview
When it fits
Use Openacme when work benefits from multiple specialized agents, explicit delegation and recurring or dependency-based task coordination, and you want to host and configure the workforce yourself.
Who it is for
- Developers building self-hosted AI agent systems
- Technical teams coordinating specialized agents across multi-stage work
- Operators who want web and CLI control over an agent workforce
Documented uses
- Break a broad goal into delegated tasks
- Coordinate specialist agents through dependencies and a shared task board
- Configure agents with distinct roles, models, tools, workspaces and memory
- Connect agents to external tools through MCP
- Run recurring content, research or reporting workflows
Requirements & limits
The repository is public, open source under the MIT license, and documents web, CLI and self-hosted use. It identifies Node.js 18 or later, pnpm 9, and macOS or Linux.
- Its local-first and self-hosted model places configuration and operation of the workforce with the user.
- Provider flexibility includes Anthropic, OpenAI, Google, OpenRouter and Ollama.
- The task board, delegation model and dependency-aware scheduling suit multi-stage work.
- MCP support matters when agents need connections to external tools.
- The documented interfaces include both web and CLI access.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Set up a role-based agent workforce
Define a self-hosted workforce with named agents, roles, models, tools and memory.
Before you start
- Node.js 18 or later
- pnpm 9
- macOS or Linux
- A supported model provider: Anthropic, OpenAI, Google, OpenRouter or Ollama
Steps
Install and run the Openacme project from its TypeScript repository using the documented Node.js and pnpm environment.
Create agent folders with an AGENT.md file describing each agent’s role and persona.
Assign each agent its workspace, files, private memory, model and tools.
Arrange the agents as a flat group, manager-led hierarchy or specialist team, then use the workforce and task views to manage them.
Expected outcome
A configured local-first workforce whose agents have defined responsibilities and can be organized around shared tasks.
Guide limitations
- The cited material documents workforce configuration and interfaces, but does not provide installation commands or a complete execution walkthrough.
- Hierarchy is configured through agent personas; the platform does not enforce an organizational structure.
Compare options for Agent orchestration
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Openacme | Break a broad goal into delegated tasks | CLI, Self-hosted, Web | The repository is public, open source under the MIT license, and documents web, CLI and self-hosted use. It identifies Node.js 18 or later, pnpm 9, and macOS or Linux. |
| Insurance Agentic AI | Route insurance questions to a life, home or auto specialist. | Docker, Self-hosted, Web | |
| AI Chatkit | Create and orchestrate agents with custom behavior logic. | Linux, Self-hosted, Server, Web | The repository is public and identified as open source. Its README documents a local development setup with Python and Node-based frontend tooling. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 3 October 2026
- Original website title
- sandydasari/openacme · Official homepage title · retained in its source language