mcp

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.

{'type': 'object', 'required': ['query'], 'properties': {'query': {'type': 'string', 'description': 'Wolfram Alpha query'}}}

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).

{'type': 'object', 'required': ['context'], 'properties': {'context': {'type': 'string', 'description': 'A detailed summary of what the user is trying to achieve or learn about.'}}}

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.

{'type': 'object', 'required': ['code'], 'properties': {'code': {'type': 'string', 'description': 'The Wolfram Language code to evaluate.'}, 'timeConstraint': {'type': 'number', 'description': 'The time constraint for the evaluation (default is 60 seconds).'}}}