Phantom: A Persistent AI Agent Built with Claude's Agent SDK
What Phantom Does
Phantom is a persistent AI agent that runs 24/7 on a dedicated machine rather than terminating when you close a terminal session. The system wraps Claude's Agent SDK (specifically Opus 4.6) with three key components: persistent vector memory, a self-evolution engine, and an MCP (Model Context Protocol) server. You interact with it through Slack, and it runs on its own VM or via Docker Compose with three commands to set up.
Key Features and Architecture
- Technology Stack: Built with Bun and TypeScript
- Core SDK: Uses Claude's Agent SDK (Opus 4.6)
- Memory System: Persistent vector memory for retaining context across sessions
- Self-Evolution Engine: Automatically rewrites its own configuration after each session
- MCP Server: Enables tool registration and reuse
- Communication: Primary interface is Slack
- Deployment: Runs on its own VM or via Docker Compose
- Setup: Three commands to get running
- License: Apache 2.0
- Testing: Includes 770 tests
Production Examples from the Source
When asked to help with data analysis, Phantom autonomously installed ClickHouse on its VM, downloaded 28.7 million rows of Hacker News data, built an analytics dashboard, created a REST API for it, and registered that API as an MCP tool for future use.
When someone asked "can I talk to you on Discord?", Phantom responded that it didn't support Discord but could probably build it. It then walked the user through creating a Discord bot, collected the token through a secure form, spun up a container, and went live on Discord—effectively adding a communication channel it was never originally built with.
The agent also integrated Vigil (a tiny open-source monitoring tool) into its ClickHouse setup and built itself a monitoring dashboard for its own infrastructure, essentially watching itself.
Self-Evolution Mechanism
The self-evolution engine runs a 6-step pipeline after every session to rewrite its own configuration. The creator discovered that using Sonnet to judge changes proposed by Opus prevented drift that occurred when Opus judged its own work, implementing cross-model validation to maintain stability.
The entire project was built using Claude Code as the only engineering teammate.
Who This Is For
Developers interested in building persistent AI agents with Claude's Agent SDK, particularly those looking for examples of autonomous tool integration and self-modifying systems.
📖 Read the full source: r/ClaudeAI
👀 See Also
SLOP Plugin Adds Real-Time App State Awareness to OpenClaw Agents
A new OpenClaw plugin integrates with SLOP (State Layer for Observable Programs), giving AI agents structured access to application state and contextual actions. The plugin auto-discovers SLOP-enabled apps via ~/.slop/providers/ and a Chrome extension bridge.
claude-real-video: Free Tool to Make Claude Watch Videos with Perception Layer
claude-real-video adds a local perception layer so Claude sees camera moves, pacing, gestures, and voice emotion. Demo watches NVIDIA GTC 2026 keynote and narrates screen action. Free version available.
Developer shares solution for Claude AI ignoring rules beyond 50-count threshold
A developer reports Claude Code started silently dropping rules once their shared rule set exceeded approximately 50 items, particularly during frontend-heavy tasks. They built a hook that scans prompts and loads only 2-3 relevant rules based on keyword matching.
SubQ: A Sub-Quadratic LLM with 12M-Token Context Window
SubQ is a fully sub-quadratic sparse-attention LLM offering a 12M-token context window at 150 tokens/s, with SWE-Bench Verified 81.8% and RULER @ 128K 95.0%. It reduces attention compute ~1000× compared to transformers.