Wolfram MCP Integration for AI Agents

Uses semantic search to retrieve any relevant information from Wolfram. Always use this tool at the start of new conversations or if the topic changes to ensure you have up-to-date relevant information. This uses semantic search, so the context argument should be written in natural language (not a search query) and contain as much detail as possible (up to 250 words).

Evaluates Wolfram Language code for the user in a Wolfram Language kernel. If a formatted result is provided as a markdown link, use that in your response instead of typing out the output. Parse natural language input with `\[FreeformPrompt]["query"]`, which is analogous to ctrl+= input in notebooks. Natural language input is parsed before evaluation, so it works like macro expansion. You should ALWAYS use this natural language input to obtain things like `Quantity`, `DateObject`, `Entity`, etc. This is a stateless kernel, so you cannot reuse definitions from previous evaluations.

Use natural language queries with Wolfram|Alpha to get up-to-date computational results about entities in chemistry, physics, geography, history, art, astronomy, and more.