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IntelliGlow Smart Lighting

This MCP server provides intelligent smart lighting control through UDP network communication, enabling AI assistants to discover, connect to, and control physical smart bulbs on local networks with voice command integration. Built with Python using asyncio and FastMCP, it offers comprehensive bulb management including network discovery across IP ranges, real-time status monitoring, RGB color control, brightness adjustment, and power management through UDP packet communication. The implementation features automatic bulb discovery, persistent connection management, voice interface integration with speech recognition, and robust error handling with retry mechanisms, making it valuable for home automation workflows, IoT device management, and voice-controlled lighting systems where AI assistants need direct hardware integration.

Cognium trust score

72%

Tier

Verified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.

Scan details: Circle-IR · 2026-09-28 · Appeal

View full trust & usage report →

Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: iot-hardware
Source: PulseMCP
Repository: github.com/shree-bd/intelliglow-ai-voice-mcp-iot-platform
Author type: human
Last scanned: 2026-09-28
Updated: 2026-09-28

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MCP

Resolve IntelliGlow Smart Lighting from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"