Enable ESP32-S3 to reach api.telegram.org and api.anthropic.com through an HTTP CONNECT proxy (e.g. Clash Verge), required in regions where these services are blocked. - New proxy module (http_proxy.c/h): CONNECT tunnel + TLS via esp_tls with pre-connected socket injection (esp_tls_set_conn_sockfd) - Telegram and LLM modules split into direct/proxy paths - CLI commands: set_proxy <host> <port>, clear_proxy - Proxy config persisted in NVS - Fix TLS buffer: MBEDTLS_SSL_IN_CONTENT_LEN 4096 → 16384 - Increase task stacks for TLS overhead (poll 12KB, agent 12KB, outbound 8KB) - Default model changed to claude-opus-4-6 - Capture raw error body for non-200 API responses Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
MimiClaw: Pocket AI Assistant on a $5 Chip
The world's first AI assistant on a $5 chip. No Linux. No Node.js. Just pure C
MimiClaw turns a tiny ESP32-S3 board into a personal AI assistant. Plug it into USB power, connect to WiFi, and talk to it through Telegram — it handles any task you throw at it and evolves over time with local memory — all on a chip the size of a thumb.
Meet MimiClaw
- Tiny — No Linux, no Node.js, no bloat — just pure C
- Handy — Message it from Telegram, it handles the rest
- Loyal — Learns from memory, remembers across reboots
- Energetic — USB power, 0.5 W, runs 24/7
- Lovable — One ESP32-S3 board, $5, nothing else
How It Works
┌─────────────── Agent Loop ───────────────┐
│ │
┌───────────┐ ┌─────▼─────┐ ┌─────────┐ ┌─────────┐ │
│ Channels │ │ Message │ │ Claude │ │ Tools │ │
│ │────▶│ Queue │────▶│ (LLM) │────▶│ │──┘
│ Telegram │ └───────────┘ └────┬─────┘ └────┬────┘
│ WebSocket │◀──────────────────────────-│ │
└───────────┘ Response │ │
┌─────▼────────────────▼────┐
│ Context │
│ ┌──────────┐ ┌────────┐ │
│ │ Memory │ │ Skills │ │
│ │ SOUL.md │ │ OTA │ │
│ │ USER.md │ │ CLI │ │
│ │ MEMORY.md │ │ ... │ │
│ └──────────┘ └────────┘ │
└───────────────────────────┘
ESP32-S3 Flash
You send a message on Telegram. The ESP32-S3 picks it up over WiFi, feeds it into an agent loop — Claude thinks, calls tools, reads memory — and sends the reply back. Everything runs on a single $5 chip with all your data stored locally on flash.
Quick Start
What You Need
- An ESP32-S3 dev board with 16 MB flash and 8 MB PSRAM (e.g. Xiaozhi AI board, ~$10)
- A USB Type-C cable
- A Telegram bot token — talk to @BotFather on Telegram to create one
- An Anthropic API key — from console.anthropic.com
Install
# You need ESP-IDF installed first:
# https://docs.espressif.com/projects/esp-idf/en/stable/esp32s3/get-started/
git clone https://github.com/memovai/mimiclaw.git
cd mimiclaw
idf.py set-target esp32s3
idf.py build
idf.py -p /dev/ttyACM0 flash monitor
Set Up
After flashing, a serial console appears. Type these commands:
mimi> wifi_set YourWiFiName YourWiFiPassword
mimi> set_tg_token 123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11
mimi> set_api_key sk-ant-api03-xxxxx
mimi> restart
That's it. After restart, find your bot on Telegram and start chatting.
More Commands
mimi> wifi_status # am I connected?
mimi> set_model claude-sonnet-4-5-20241022 # use a different model
mimi> memory_read # see what the bot remembers
mimi> heap_info # how much RAM is free?
mimi> session_list # list all chat sessions
mimi> session_clear 12345 # wipe a conversation
mimi> restart # reboot
Memory
MimiClaw stores everything as plain text files you can read and edit:
| File | What it is |
|---|---|
SOUL.md |
The bot's personality — edit this to change how it behaves |
USER.md |
Info about you — name, preferences, language |
MEMORY.md |
Long-term memory — things the bot should always remember |
2026-02-05.md |
Daily notes — what happened today |
tg_12345.jsonl |
Chat history — your conversation with the bot |
Also Included
- WebSocket gateway on port 18789 — connect from your LAN with any WebSocket client
- OTA updates — flash new firmware over WiFi, no USB needed
- Dual-core — network I/O and AI processing run on separate CPU cores
For Developers
Technical details live in the docs/ folder:
- docs/ARCHITECTURE.md — system design, module map, task layout, memory budget, protocols, flash partitions
- docs/TODO.md — feature gap tracker and roadmap
License
MIT
Acknowledgments
Inspired by OpenClaw. MimiClaw reimplements the core AI agent architecture for embedded hardware — no Linux, no server, just a $5 chip.
