MCP server for Wolfram Alpha computations
## Wolfram Alpha MCP Server: Computational Intelligence for Development The **Wolfram Alpha MCP Server** brings the world's most powerful computational knowledge engine directly into Google Antigravity, enabling AI assistants to perform complex calculations, access curated data, and solve problems across mathematics, science, engineering, and beyond. This integration transforms your IDE into a computational powerhouse for data-driven development. ### Why Wolfram Alpha MCP? - **Computational Answers**: Get computed results rather than search results—actual solutions to mathematical and scientific queries - **Curated Knowledge**: Access expertly curated data across thousands of domains from physics to finance - **Natural Language Input**: Express complex queries in plain English and receive structured, computable answers - **Step-by-Step Solutions**: Understand the process behind calculations with detailed solution breakdowns - **Real-Time Data**: Access current information on weather, stocks, geography, and more for dynamic applications ### Key Features #### 1. Mathematical 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 eigenvalues of the matrix [[1,2],[3,4]] and explain their significance" }], tools=[{ "name": "wolfram_compute", "description": "Perform mathematical computations" }] ) ``` #### 2. Data Queries ```python # Access curated datasets response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Get the population density of major European cities for my visualization" }], tools=[{"name": "wolfram_data", "description": "Query curated knowledge base"}] ) ``` #### 3. Unit Conversions ```python # Complex unit conversions and comparisons response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Convert 1.5 petabytes per second to human-readable terms with comparisons" }], tools=[{"name": "wolfram_convert", "description": "Convert and compare units"}] ) ``` #### 4. Algorithm Analysis ```python # Analyze computational complexity response = client.messages.create( model="claude-sonnet-4-20250514", max_tokens=1024, messages=[{ "role": "user", "content": "Compare the time complexity of quicksort vs mergesort for n=1000000" }], tools=[{"name": "wolfram_analyze", "description": "Computational analysis"}] ) ``` ### Configuration ```json { "mcpServers": { "wolfram-alpha": { "command": "npx", "args": ["-y", "@anthropic/mcp-wolfram"], "env": { "WOLFRAM_APP_ID": "your-wolfram-app-id" } } } } ``` ### Use Cases **Algorithm Development**: Verify mathematical foundations, test edge cases, and validate computational assumptions during algorithm design. **Data Validation**: Cross-reference application calculations against authoritative sources for financial, scientific, or engineering software. **Scientific Computing**: Access physical constants, chemical properties, and astronomical data for simulation and modeling applications. **Educational Tools**: Build learning applications with step-by-step solutions and explanations for mathematical concepts. The Wolfram Alpha MCP Server elevates your development environment with computational intelligence, bringing 50+ years of curated knowledge to every coding session.
{
"mcpServers": {
"wolfram-alpha": {
"mcpServers": {
"wolfram-alpha": {
"env": {
"WOLFRAM_API_KEY": "YOUR_WOLFRAM_API_KEY"
},
"args": [
"wolfram-alpha-mcp-server"
],
"command": "uvx"
}
}
}
}
}