Structured knowledge from Wolfram Alpha
## Wolfram LLM MCP Server: Computational Knowledge for AI The **Wolfram LLM MCP Server** integrates Wolfram's computational knowledge specifically optimized for large language model interactions directly into Google Antigravity. This specialized integration enables AI assistants to perform complex computations, access curated data, and leverage Wolfram's knowledge base with responses formatted for AI consumption. ### Why Wolfram LLM MCP? - **LLM-Optimized Responses**: Receive computational results formatted specifically for AI assistant interpretation - **Natural Language Math**: Express complex mathematical queries in plain English with accurate symbolic computation - **Structured Data Access**: Access Wolfram's curated knowledge base with responses optimized for further processing - **Step-by-Step Explanations**: Get detailed breakdowns of calculations suitable for explaining to users - **Real-Time Computation**: Perform live calculations on current data including financial, scientific, and geographic ### Key Features #### 1. Natural Language Computation ```python from anthropic import Anthropic client = Anthropic() response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Calculate the compound interest on $10,000 at 5% over 10 years with monthly compounding" }], tools=[{ "name": "wolfram_llm_compute", "description": "Perform computational queries" }] ) ``` #### 2. Data Queries ```python # Query structured knowledge response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Get the GDP, population, and area of the 10 largest economies" }], tools=[{"name": "wolfram_llm_data", "description": "Query knowledge base"}] ) ``` #### 3. Scientific Calculations ```python # Complex scientific computation response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Calculate the orbital period of a satellite at 400km altitude above Earth" }], tools=[{"name": "wolfram_llm_science", "description": "Scientific computations"}] ) ``` #### 4. Code Generation ```python # Generate code from math response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Convert this statistical formula into Python code with explanation" }], tools=[{"name": "wolfram_llm_code", "description": "Generate code from computation"}] ) ``` ### Configuration ```json { "mcpServers": { "wolfram-llm": { "command": "npx", "args": ["-y", "@anthropic/mcp-wolfram-llm"], "env": { "WOLFRAM_LLM_API_KEY": "your-wolfram-llm-api-key" } } } } ``` ### Use Cases **Data Analysis Applications**: Integrate computational verification and statistical analysis into data science tools. **Educational Platforms**: Build learning applications that show step-by-step mathematical solutions. **Financial Calculators**: Create accurate financial tools with complex interest, amortization, and investment calculations. **Scientific Software**: Add computational capabilities for physics, chemistry, and engineering calculations. The Wolfram LLM MCP Server brings computational intelligence specifically designed for AI assistants, enabling accurate calculations and knowledge access in your applications.
{
"mcpServers": {
"wolfram-llm": {
"mcpServers": {
"wolfram-llm": {
"env": {
"WOLFRAM_API_KEY": "YOUR_API_KEY"
},
"args": [
"-y",
"@henryhawke/wolfram-llm-mcp"
],
"command": "npx"
}
}
}
}
}