AI assistants

Use ReliaSim® From Claude or ChatGPT
The Assistant Asks the Engine, So the Numbers Come From the Simulation

Ask a general AI assistant how much a buffer would add to your line and it will give you a confident number with no model behind it. Connect it to ReliaSim and it can look the answer up instead. It calls ReliaSim’s tools, gets results the simulation engine produced, and quotes them.

Why connect an assistant to a simulation

A language model is good at explaining, summarizing and answering follow-up questions. It can’t simulate your line, because it has no model of the line to run. When it answers a what-if question on its own, the number is a plausible guess. Why an AI can’t answer what-if goes into the reasons.

The Model Context Protocol (MCP) lets an assistant call outside tools during a conversation. ReliaSim publishes an MCP server, so the assistant can ask for a bottleneck analysis or a buffer sweep and get back results from the engine.

What a conversation looks like

Ask about your line: where it’s held back, what a bigger buffer would do, which fix pays first. You drive the conversation and the model does the math. From one conversation you can:

Here is one exchange about the 90-day run of the bottling line.

Bottling line, 90-day run
ReliaSim AI · Bottling Line
You
The model matches our 54.3% OEE. Which fix should we make first?
ReliaSim
Not the one the Loss Tree ranks first. Labeler Misalignment costs 6.79% and Filler Micro Stop costs 6.72%, nearly a tie. Removing each one in the model, the Labeler fix gives back +5.0 points and the Filler fix gives back +8.1, 62% more, because the Filler’s short stops ripple into every machine after it. Start with the Filler.
You
Could a buffer after the Filler do the same job without touching the machine?
ReliaSim
It can soak up some of those short stops. Run the buffer trade-off on this line against the Filler fix and the model shows which one gives back more output for the money. Both answers come from the same playing field.

Every response comes from the model’s own engine runs. It works with Claude, Claude Code and any MCP-compatible assistant.

What the ReliaSim server can answer

The public server at https://reliasim.com/mcp covers the eight reference bottling-line models in the Sandbox. Its tools return saved results from ReliaSim engine runs on those models:

Each tool tells the assistant to quote its numbers as returned. The server doesn’t need an API key or an account.

Connect from Claude

In Claude on the web or the desktop app, add a custom connector in your connector settings and paste the server URL:

https://reliasim.com/mcp

In Claude Code, add it from the terminal:

claude mcp add --transport http reliasim https://reliasim.com/mcp

Other MCP clients, such as Cursor, take the same URL. Custom connectors depend on your plan and on your workspace settings.

Connect from ChatGPT

ChatGPT can use a remote MCP server as a custom connector where your plan and workspace allow it. Add a connector, give it the same URL, and choose no authentication. If you don’t see the option, your workspace admin may need to turn on custom connectors first.

Questions to try

If the answer includes a number, ask the assistant which tool it came from. A good answer names the tool and the model.

Stop-data statistics from ReliaStats

A second server covers the statistics side: Weibull shape, availability, distribution choice and how to read validation bands. It lives at https://reliasim.com/reliastats/mcp/v1 and connects the same way. See ReliaStats for the browser tools it pairs with.

Or use the assistant in the Sandbox

Every demo in the Sandbox has an assistant beside it that answers from that demo’s own results, including the supply chain networks. It’s the quickest way to see the approach before you connect anything. What each Sandbox tier covers. For your own line or network, the models are built from your data as a project. How a ReliaSim project runs shows the steps.

Add ReliaSim to your assistant

One URL, no key: https://reliasim.com/mcp. It’s a live JSON-RPC endpoint, and setup is in the documentation.

See the MCP endpoint →