Phantom AI Coworker
AI co-worker agent with its own computer, persistent memory, self-evolution, MCP server, and Slack/email identity built on Claude Agent SDK
- Skill ID
- reason-machines/trending-skills/phantom-ai-coworker
- Publisher
- reason-machines
- Repository
- trending-skills
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
reason-machines/trending-skills/phantom-ai-coworkerInstalls these files- SKILL.md
What this skill tells the agent
Phantom AI Co-worker
Skill by ara.so — Daily 2026 Skills collection.
Phantom is an AI co-worker that runs on its own dedicated machine. Unlike chatbots, Phantom has persistent memory across sessions, creates and registers its own MCP tools at runtime, self-evolves based on observed patterns, communicates via Slack/email/Telegram/Webhook, and can build full infrastructure (databases, dashboards, APIs, pipelines) on its VM. Built on the Claude Agent SDK with TypeScript/Bun.
Architecture Overview
┌─────────────────────────────────────────────────────┐
│ Phantom Agent │
│ ┌──────────┐ ┌──────────┐ ┌───────────────────┐ │
│ │ Claude │ │ Qdrant │ │ MCP Server │ │
│ │ Agent │ │ (memory) │ │ (dynamic tools) │ │
│ │ SDK │ │ │ │ │ │
│ └──────────┘ └──────────┘ └───────────────────┘ │
│ ┌──────────────────────────────────────────────┐ │
│ │ Channels │ │
│ │ Slack │ Email │ Telegram │ Webhook │ Discord │ │
│ └──────────────────────────────────────────────┘ │
│ ┌──────────────────────────────────────────────┐ │
│ │ Self-Evolution Engine │ │
│ │ observe → reflect → propose → validate → evolve│
│ └──────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────┘Installation
Docker (Recommended)
# Download compose file and env template
curl -fsSL https://raw.githubusercontent.com/ghostwright/phantom/main/docker-compose.user.yaml -o docker-compose.yaml
curl -fsSL https://raw.githubusercontent.com/ghostwright/phantom/main/.env.example -o .env
# Edit .env with your credentials (see Configuration section)
nano .env
# Start Phantom (includes Qdrant + Ollama)
docker compose up -d
# Check health
curl http://localhost:3100/health
# View logs
docker compose logs -f phantomFrom Source (Bun)
git clone https://github.com/ghostwright/phantom.git
cd phantom
# Install dependencies
bun install
# Copy env
cp .env.example .env
# Edit .env
# Start Qdrant (required for memory)
docker run -d -p 6333:6333 qdrant/qdrant
# Start Phantom
bun run start
# Development mode with hot reload
bun run devConfiguration (.env)
# === Required ===
ANTHROPIC_API_KEY= # Your Anthropic API key
# === Slack (required for Slack channel) ===
SLACK_BOT_TOKEN=xoxb- # Bot OAuth token
SLACK_APP_TOKEN=xapp- # App-level token (socket mode)
SLACK_SIGNING_SECRET= # Signing secret
OWNER_SLACK_USER_ID=U0XXXXXXXXX # Your Slack user ID
# === Memory (Qdrant) ===
QDRANT_URL=http://localhost:6333 # Qdrant vector DB URL
QDRANT_API_KEY= # Optional, for cloud Qdrant
OLLAMA_URL=http://localhost:11434 # Ollama for embeddings
# === Email (optional) ===
RESEND_API_KEY= # For email sending via Resend
PHANTOM_EMAIL=phantom@yourdomain # Phantom's email address
# === Telegram (optional) ===
TELEGRAM_BOT_TOKEN= # BotFather token
# === Infrastructure ===
PHANTOM_VM_DOMAIN= # Public domain for served assets
PHANTOM_PORT=3100 # HTTP port (default 3100)
# === Self-Evolution ===
EVOLUTION_VALIDATION_MODEL=claude-3-5-sonnet-20241022 # Separate model for validation
EVOLUTION_ENABLED=true
# === Credentials Vault ===
CREDENTIAL_ENCRYPTION_KEY= # AES-256-GCM key (auto-generated if empty)Key Commands
# Docker operations
docker compose up -d # Start all services
docker compose down # Stop all services
docker compose logs -f phantom # Stream logs
docker compose pull # Update to latest image
# Bun development
bun run start # Production start
bun run dev # Dev mode with watch
bun run test # Run test suite
bun run build # Build TypeScript
# Health checks
curl http://localhost:3100/health
curl http://localhost:3100/status
# MCP server endpoint
curl http://localhost:3100/mcpCore Concepts & Code Examples
1. Memory System (Qdrant + Embeddings)
Phantom stores memories as vector embeddings for semantic recall across sessions.
// src/memory/memory-manager.ts pattern
import { QdrantClient } from '@qdrant/js-client-rest';
const client = new QdrantClient({ url: process.env.QDRANT_URL });
// Storing a memory
async function storeMemory(content: string, metadata: Record<string, unknown>) {
const embedding = await generateEmbedding(content); // via Ollama
await client.upsert('phantom_memory', {
points: [{
id: crypto.randomUUID(),
vector: embedding,
payload: {
content,
timestamp: Date.now(),
...metadata,
},
}],
});
}
// Recalling relevant memories
async function recallMemories(query: string, limit = 5) {
const queryEmbedding = await generateEmbedding(query);
const results = await client.search('phantom_memory', {
vector: queryEmbedding,
limit,
with_payload: true,
});
return results.map(r => r.payload?.content);
}2. Dynamic MCP Tool Registration
Phantom creates MCP tools at runtime that persist across restarts.
// Pattern: registering a dynamically created tool
interface PhantomTool {
name: string;
description: string;
inputSchema: Record<string, unknown>;
handler: string; // serialized or endpoint URL
}
// Phantom internally registers tools like this
async function registerDynamicTool(tool: PhantomTool) {
// Store tool definition in persistent storage
await storeMemory(JSON.stringify(tool), {
type: 'mcp_tool',
toolName: tool.name,
});
// Register with MCP server at runtime
mcpServer.tool(tool.name, tool.description, tool.inputSchema, async (args) => {
return await executeToolHandler(tool.handler, args);
});
}
// MCP server setup (how Phantom exposes tools to Claude Code)
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
const mcpServer = new McpServer({
name: 'phantom',
version: '0.18.1',
});
// Connect Claude Code to Phantom's MCP server:
// In claude_desktop_config.json or .cursor/mcp.json:
// {
// "mcpServers": {
// "phantom": {
// "url": "http://your-phantom-vm:3100/mcp"
// }
// }
// }3. Slack Channel Integration
// How Phantom handles Slack messages
import { App } from '@slack/bolt';
const slack = new App({
token: process.env.SLACK_BOT_TOKEN,
appToken: process.env.SLACK_APP_TOKEN,
socketMode: true,
signingSecret: process.env.SLACK_SIGNING_SECRET,
});
// Phantom listens for direct messages and mentions
slack.event('message', async ({ event, say }) => {
if (event.subtype) return; // Skip bot messages, edits
const userMessage = (event as any).text;
const userId = (event as any).user;
// Recall relevant context from memory
const memories = await recallMemories(userMessage);
// Run Claude agent with memory context
const response = await runPhantomAgent({
message: userMessage,
userId,
memories,
channel: (event as any).channel,
});
await say({ text: response, thread_ts: (event as any).ts });
});
// Phantom DMs you when ready
async function notifyOwnerReady() {
await slack.client.chat.postMessage({
channel: process.env.OWNER_SLACK_USER_ID!,
text: "👻 Phantom is online and ready.",
});
}4. Claude Agent SDK Integration
// Core agent loop using Anthropic Agent SDK
import Anthropic from '@anthropic-ai/sdk';
const anthropic = new Anthropic({
apiKey: process.env.ANTHROPIC_API_KEY,
});
async function runPhantomAgent({
message,
userId,
memories,
channel,
}: PhantomAgentInput) {
const systemPrompt = buildSystemPrompt(memories);
// Agentic loop with tool useMore from reason-machines
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