Option A: Connect via the Anthropic Connectors Directory (recommended for Claude.ai)
If you found UniversalBench in the Claude.ai connectors directory, just click Connect. The OAuth flow handles everything. You will be asked to sign in or create an account, then Claude.ai is connected automatically. No URL to copy, no config file to edit. That is it. Skip to Run your first call.Option B: Connect with a personal URL (Claude Desktop, Cursor, Claude Code, custom agents)
For any MCP client outside of Claude.ai, sign up at universalbench.dev. After you verify your email, your dashboard shows your personal MCP URL:- Claude Desktop
- Cursor
- Claude Code
- Direct HTTP
Edit Restart Claude Desktop. UniversalBench appears in the tool list within seconds.
~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows:Run your first call
Ask your AI something that requires execution:Use UniversalBench to find all prime numbers under 10,000 and tell me the largest gap between consecutive primes.Your AI routes the heavy lifting to UniversalBench, which runs the Python and returns just the answer. Your AI synthesizes a clean response from a small result instead of generating thousands of tokens in its own context.
What to try next
Web search with live data
Ask your AI to search the web for current information. UniversalBench returns clean snippets with sources.
Invoke any LLM
Use
invoke_llm to call models from any provider on demand. Compare outputs, route by cost, or run a cheap model as a first pass.Keep state across calls
Pass
session_id so your Python variables and imports persist between calls. Build a dataframe once, query it many times.Store secrets safely
Use
secrets_vault to store API keys encrypted server side. Your AI uses them by name without ever seeing the value.