Wolfram Alpha
Connect your chat repl to wolfram alpha computational intelligence
Installation
Installing for Claude Desktop
Option 1: One-Command Installation
npx mcpbar install SecretiveShell/MCP-wolfram-alpha -c claude
This command will automatically install and configure the Wolfram Alpha MCP server for your selected client.
Option 2: Manual Configuration
View JSON configuration
{
"mcpServers": {
"Wolfram Alpha": {
"command": "uv",
"args": [
"--directory",
"C:\\Users\\root\\Documents\\MCP-wolfram-alpha",
"run",
"MCP-wolfram-alpha"
],
"env": {
"WOLFRAM_API_KEY": "your-app-id"
}
}
}
}
Copy and paste this configuration into your MCP client's configuration file to manually set up this server.
Common MCP clients
claude
- Claude Desktopcursor
- Cursor Code Editorcline
- Cline (VS Code)windsurf
- Windsurf Editorwitsy
- Witsy AI Assistant
MCP-wolfram-alpha
A MCP server to connect to wolfram alpha API.
Components
Prompts
This is analogous to the !wa
bang in duckduckgo search.
def wa(query: str) -> f"Use wolfram alpha to answer the following question: {query}"
Tools
Query Wolfram Alpha api.
def query_wolfram_alpha(query: str) -> str
Configuration
You must set the WOLFRAM_API_KEY
environment variable. Get an api ket from Wolfram Alpha.
This was tested with the full results API, but it might not be required.
{
"mcpServers": {
"MCP-wolfram-alpha": {
"command": "uv",
"args": [
"--directory",
"C:\\Users\\root\\Documents\\MCP-wolfram-alpha",
"run",
"MCP-wolfram-alpha"
],
"env": {
"WOLFRAM_API_KEY": "your-app-id"
}
}
}
}
Development
Debugging
Since the official MCP inspector does not have good environment support, I reccommend using wong2's mcp-cli-inspector.
Create a config.json file in the same style as claude desktop.
{
"mcpServers": {
"MCP-wolfram-alpha": {
"command": "uv",
"args": [
"--directory",
"/full/path/to/MCP-wolfram-alpha",
"run",
"MCP-wolfram-alpha"
],
"env": {
"WOLFRAM_API_KEY": "your-app-id"
}
}
}
}
Then run:
npx @wong2/mcp-cli -c .\config.json
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