ReasonForge MCP Server

Example Use Cases

• 1

  Perform verified symbolic math computations reliably.

• 2

  Execute and verify Python code safely in a sandboxed environment.

• 3

  Improve accuracy and reduce latency in math and code problem solving.

Description

ReasonForge enables small LLMs (8B–32B) to perform reliable mathematical computations and code execution by delegating tasks to deterministic backends like SymPy and a sandboxed Python runtime. This approach improves accuracy, reduces latency, and allows iterative reasoning with verified results. It supports multi-turn tool calling for math, calculus, matrix operations, statistics, and code execution, enhancing the capabilities of smaller models without fine-tuning.