PLCs.ai

Name: PLCs.ai
Author: PLCsai

Query Allen-Bradley and Siemens PLC projects, live tag values, and analyses in plain English.

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Install

mcp_config.json

{
  "mcpServers": {
    "ai-plcs-plcs-ai": {
      "url": "https://mcp.plcs.ai/mcp",
      "type": "streamable-http"
    }
  }
}

Documentation

PLCs.ai MCP Server

Connect Claude, Cursor, Codex, or any MCP-compatible agent to your PLC projects.

PLCs.ai is the AI platform purpose-built for PLC engineers: upload an Allen-Bradley (Studio 5000) or Siemens (TIA Portal) project and understand, troubleshoot, document, and safely generate code for it in plain English. This MCP server gives any AI agent governed access to that same capability — your projects, live tag values, and analyses — with per-tool permission scopes.

Remote server: https://mcp.plcs.ai/mcp (Streamable HTTP · OAuth or API key) Full documentation: https://www.plcs.ai/developer/mcp

Quick start

Claude Code

claude mcp add --transport http plcs-ai https://mcp.plcs.ai/mcp

Then run /mcp and choose Authenticate to sign in with your PLCs.ai account. (Or pass an API key: --header "Authorization: Bearer plck_live_…".)

Claude Desktop

Settings → Connectors → Add custom connector → URL https://mcp.plcs.ai/mcp → Connect and sign in. For API-key or on-prem setups, use the mcp-remote bridge:

{
  "mcpServers": {
    "plcs-ai": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.plcs.ai/mcp",
               "--header", "Authorization: Bearer plck_live_…"]
    }
  }
}

Cursor / Codex / other MCP clients

See per-client guides: https://www.plcs.ai/developer/mcp — covers Cursor, Codex, and any client that speaks remote MCP or can run mcp-remote.

What the agent can do

19 tools, permission-scoped per API key or OAuth grant:

Area	Tools
Discover	`plcs_health`, `plcs_list_projects`, `plcs_get_project`, `plcs_get_project_source`
Understand	`plcs_interpret`, `plcs_search_context`
Live plant data	`plcs_get_live_values`, `plcs_get_tag_history`
Analyze	`plcs_start_analysis`, `plcs_get_analysis` (dead code, race conditions, missing handshakes, interlock audits, cycle-time bottlenecks, signal tracing)
Generate	`plcs_generate_code` — returns a reviewable proposal; nothing is saved without review
Version & export	`plcs_save_version`, `plcs_ingest_project`, `plcs_stage_upload`, `plcs_export_plc`, `plcs_export_pdf`, `plcs_get_export`, `plcs_download_export`
Embed	`plcs_mint_embed_token` — short-lived, read-only, project-scoped iframe tokens

Example prompts

"List my PLC projects and check which ones have live data connected."
"Why won't Conveyor 3 restart after a stop? Trace the interlocks."
"Run a dead-code analysis on the Palletizer project and summarize what's safe to remove."
"What did tag Motor1_Enable do in the last hour?"
"Draft a fix for the missing handshake between Conv001 and Rob010 — proposal only."

Safety model

Every tool call is authenticated and scoped to your organization; the credential is the tenant.
Code generation returns proposals; persisting a new version is a separate, separately-scoped action.
Customer data is never used to train AI models. Data handling →

Requirements

A PLCs.ai account (start a free trial) or API key
For the mcp-remote bridge: Node 18+

Sourced from the repository README.

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