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Litmus Edge

This MCP server provides integration with Litmus Edge for industrial IoT device configuration, monitoring, and management, enabling AI assistants to interact with DeviceHub devices, retrieve real-time tag values, manage Docker containers, and configure system settings. Built by Litmus Automation using Python with FastMCP and featuring both stdio and HTTP transport modes, it offers tools for listing supported drivers, creating and managing DeviceHub devices with various protocols, subscribing to NATS topics for real-time data streaming, managing Docker containers through the Litmus Edge Marketplace, and configuring system properties like friendly names and cloud activation status. The implementation includes a web client interface with streaming support for real-time responses, environment variable management, conversation history tracking, and support for both Anthropic and OpenAI models, making it valuable for industrial automation workflows, IoT device management, real-time monitoring dashboards, and any use case requiring programmatic access to Litmus Edge infrastructure for industrial data collection and device orchestration.

Cognium trust score

59%

Tier

Scanned

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: cloud-infra
Source: PulseMCP
Repository: github.com/litmusautomation/litmus-mcp-server
Author type: human
Last scanned: 2026-09-28
Updated: 2026-09-28

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MCP

Resolve Litmus Edge 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"