Mcp Number Theory
Give your coding agent callable number-theory and factorization routines without hand-rolling math helpers in every project.
Overview
io.github.daedalus/mcp-number-theory is a MCP server for the Build phase that exposes number-theory functions and factorization algorithms to your agent over stdio.
What is this MCP server?
- Exposes number-theory primitives and factorization algorithms as MCP tools
- stdio transport for local Claude Code, Cursor, and other MCP clients
- PyPI package mcp-number-theory at version 0.1.0
- Open source on GitHub under daedalus/mcp-number-theory
- Composable with other daedalus math MCP servers (NumPy, PARI/GP, OEIS)
- Registry version 0.1.0
- Transport: stdio
- Package identifier: mcp-number-theory (pypi)
What problem does it solve?
Agents guess at integer factorization and number-theory steps unless you give them a real library behind MCP tools.
Who is it for?
Indie builders prototyping math-heavy features, CTF-style puzzles, or teaching apps who already use Python and MCP.
Skip if: Teams that need a full CAS/UI workflow only—use PARI/GP MCP or a dedicated math notebook instead of this focused server.
What do I get? / Deliverables
After you register the server, the agent can invoke verified factorization and number-theory operations while you stay in the editor.
- Registered stdio MCP server exposing number-theory and factorization tools
- Agent-callable factorization results usable in app code or tests
- Local math tooling without a separate web CAS session
Recommended MCP Servers
Journey fit
Canonical shelf is Build because the server is wired into the agent during product development, not a launch or ops workflow. Integrations fits MCP servers that expose external libraries as agent tools alongside your app code.
How it compares
MCP math integration over PyPI, not a packaged agent skill or a hosted SaaS API.
Common Questions / FAQ
Who is mcp-number-theory for?
Solo and indie developers who use Claude Code, Cursor, or similar MCP clients and want agents to call real number-theory and factorization code during builds.
When should I use mcp-number-theory?
Use it while implementing or debugging features that depend on primes, divisors, or factorization, especially when LLM mental math is unreliable.
How do I add mcp-number-theory to my agent?
Install the PyPI package mcp-number-theory, add a stdio MCP server entry pointing at that package in your client config, and restart the agent so tools load.