phantom — MCP Server by ghostwright

by ghostwright · MCP Server · ★ 1.4k

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About phantom

Phantom An AI co-worker with its own computer. Website · Get a Free Phantom · Docs · Issues The Idea AI agents today are disposable. You open a chat, get an answer, close the tab, and the context is gone. Next time you start from scratch. Every session is day one. Phantom takes a different approach: give the AI its own computer. A dedicated machine where it installs software, spins up databases, builds dashboards, remembers what you told it last week, and gets measurably better at your job every day. Your laptop stays yours. The agent's workspace is its own. This is not a chatbot. It is a co-worker that runs on Slack, has its own email addre

ai-agentsai-coworkeranthropicautonomous-agentsbunclaudedockerllmmcpself-evolution

Quick Facts

Stars1,400
Forks179
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score50.044/100
Open Issues43
Last Updated2026-05-02
Created2026-03-26
Platformsclaude-code, docker, mcp, node
Est. Tokens~1467k

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Frequently Asked Questions

What is phantom?

phantom is An AI co-worker with its own computer. Self-evolving, persistent memory, MCP server, secure credential collection, email identity. Built on the Claude Agent SDK.. It is categorized as a MCP Server with 1.4k GitHub stars.

What programming language is phantom written in?

phantom is primarily written in TypeScript. It covers topics such as ai-agents, ai-coworker, anthropic.

How do I install or use phantom?

You can find installation instructions and usage details in the phantom GitHub repository at github.com/ghostwright/phantom. The project has 1.4k stars and 179 forks, indicating an active community.

What license does phantom use?

phantom is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to phantom?

The top alternatives to phantom on Agent Skills Hub include open-multi-agent, oh-my-pi, awesome-openclaw-agents. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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