How do I install the Esp32 Cam Eyes skill?

Run npx skillmds@latest add dvcrn/esp32-cam-eyes in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Esp32 Cam Eyes safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Esp32 Cam Eyes?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Esp32 Cam Eyes free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Esp32 Cam Eyes?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Esp32 Cam Eyes by dvcrn — Agent Skill

Name: Esp32 Cam Eyes
Rating: 4.2 (5 reviews)
Author: dvcrn

Esp32 Cam Eyes

Set up ESP32-S3-CAM modules as visual sensors (eyes) for OpenClaw agents. Covers hardware identification, firmware flashing, WiFi configuration, and HTTP camera server deployment using PlatformIO + Arduino framework. Use when the user wants to give their agent physical vision, set up ESP32-CAM, connect a camera module, flash camera firmware, or troubleshoot ESP32-S3 camera issues. Supports Hiwonder/Freenove boards with GC2145, OV2640, and OV5640 sensors.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

ESP32-CAM Eyes

Give your OpenClaw agent physical eyes using ESP32-S3-CAM modules.

Overview

Each ESP32-CAM module runs a lightweight HTTP server exposing /capture (single JPEG snapshot) and /stream (MJPEG live stream). Once connected to WiFi, the agent can grab images via curl for vision analysis.

Prerequisites

Hardware: ESP32-S3 development board with camera sensor (Hiwonder, Freenove, or similar)
Software: macOS or Linux with Python 3 installed
Tools: PlatformIO CLI (pip3 install platformio), pyserial (pip3 install pyserial)

Quick Start

Plug in the ESP32-CAM via USB
Identify the serial port: ls /dev/cu.usb* (macOS) or ls /dev/ttyUSB* (Linux)
Identify the sensor model (critical — determines firmware config)
Create PlatformIO project, flash firmware
Connect to WiFi, test with curl -o photo.jpg http://<IP>/capture

For the complete step-by-step guide with firmware code, pin definitions, performance benchmarks, and troubleshooting: read references/setup-guide.md.

Key Decision: Sensor Type

The sensor model determines your firmware strategy:

Sensor	PID	Hardware JPEG	Recommended Format
OV2640	0x2640	✅ Yes	`PIXFORMAT_JPEG` directly
OV5640	0x5640	✅ Yes	`PIXFORMAT_JPEG` directly
GC2145	0x2145	❌ No	`PIXFORMAT_RGB565` + software `frame2jpg()`

If buying new boards, prefer OV2640 — hardware JPEG is significantly faster.

API Endpoints

Once flashed and connected:

Path	Function
`/capture`	Single JPEG snapshot
`/stream`	MJPEG live stream
`/`	Web UI with stream viewer

Multi-Camera Deployment

Multiple ESP32-CAMs can join the same WiFi network for multi-angle coverage. Bind fixed IPs via router DHCP reservation to avoid IP changes on reboot.

Common Pitfalls

Wrong sensor ID: Always verify PID before choosing firmware config
Upload speed: Use 460800 baud, not 921600 (causes flash verification failures on many boards)
WiFi band: ESP32 only supports 2.4GHz — ensure your router has a 2.4GHz SSID available
QQVGA is slower than VGA: Counter-intuitive but true due to PSRAM DMA buffer efficiency; use XGA (1024×768) for best speed/quality balance

---name: esp32-cam-eyesdescription: Set up ESP32-S3-CAM modules as visual sensors (eyes) for OpenClaw agents. Covers hardware identification, firmware flashing, WiFi configuration, and HTTP camera server deployment using PlatformIO + Arduino framework. Use when the user wants to give their agent physical vision, set up ESP32-CAM, connect a camera module, flash camera firmware, or troubleshoot ESP32-S3 camera issues. Supports Hiwonder/Freenove boards with GC2145, OV2640, and OV5640 sensors.---# ESP32-CAM EyesGive your OpenClaw agent physical eyes using ESP32-S3-CAM modules.## OverviewEach ESP32-CAM module runs a lightweight HTTP server exposing `/capture` (single JPEG snapshot) and `/stream` (MJPEG live stream). Once connected to WiFi, the agent can grab images via `curl` for vision analysis.## Prerequisites- **Hardware**: ESP32-S3 development board with camera sensor (Hiwonder, Freenove, or similar)- **Software**: macOS or Linux with Python 3 installed- **Tools**: PlatformIO CLI (`pip3 install platformio`), pyserial (`pip3 install pyserial`)## Quick Start1. Plug in the ESP32-CAM via USB2. Identify the serial port: `ls /dev/cu.usb*` (macOS) or `ls /dev/ttyUSB*` (Linux)3. Identify the sensor model (critical — determines firmware config)4. Create PlatformIO project, flash firmware5. Connect to WiFi, test with `curl -o photo.jpg http://<IP>/capture`For the complete step-by-step guide with firmware code, pin definitions, performance benchmarks, and troubleshooting: read [references/setup-guide.md](references/setup-guide.md).## Key Decision: Sensor TypeThe sensor model determines your firmware strategy:| Sensor | PID | Hardware JPEG | Recommended Format ||--------|-----|---------------|-------------------|| OV2640 | 0x2640 | ✅ Yes | `PIXFORMAT_JPEG` directly || OV5640 | 0x5640 | ✅ Yes | `PIXFORMAT_JPEG` directly || GC2145 | 0x2145 | ❌ No | `PIXFORMAT_RGB565` + software `frame2jpg()` |If buying new boards, prefer **OV2640** — hardware JPEG is significantly faster.## API EndpointsOnce flashed and connected:| Path | Function ||------|----------|| `/capture` | Single JPEG snapshot || `/stream` | MJPEG live stream || `/` | Web UI with stream viewer |## Multi-Camera DeploymentMultiple ESP32-CAMs can join the same WiFi network for multi-angle coverage. Bind fixed IPs via router DHCP reservation to avoid IP changes on reboot.## Common Pitfalls- **Wrong sensor ID**: Always verify PID before choosing firmware config- **Upload speed**: Use 460800 baud, not 921600 (causes flash verification failures on many boards)- **WiFi band**: ESP32 only supports 2.4GHz — ensure your router has a 2.4GHz SSID available- **QQVGA is slower than VGA**: Counter-intuitive but true due to PSRAM DMA buffer efficiency; use XGA (1024×768) for best speed/quality balance

Frequently asked questions