"Tools and Systems for Math, AI, and Proof Verification with Bug Detection and Auto Fixing" matching MCP servers:

Provides emergency coding assistance by querying three AI coding models simultaneously through OpenRouter, with automatic premium fallback on rate limits, returning multiple expert opinions with cost and latency telemetry for debugging and problem-solving.

An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A secure MCP server for evaluating mathematical expressions with grammar validation, function whitelisting, and sandboxed execution. It provides tools for expression evaluation, variable management, and resources for grammar and function documentation.

Provides LLMs with deterministic math tools for sandboxed expression evaluation, descriptive statistics, primality testing, prime factorization, GCD/LCM, quadratic solving, and base conversion. Every operation runs real code rather than relying on the model's arithmetic, with expression parsing restricted to a whitelist of operators, constants, and functions.

An MCP server implementing a multi-phase backend for structured model interactions, bounded compilation, exact-hash confirmation, and Codex-run provenance, with trust-separation hardening.

MCP server that gives small LLMs verified symbolic-math & logic tools.

Enables basic arithmetic operations (addition, subtraction, multiplication, division) with 64-bit precision and matrix multiplication capabilities. Provides mathematical computation tools for AI assistants through the Model Context Protocol.

A Model Context Protocol server that provides basic mathematical and statistical functions to LLMs, enabling them to perform accurate numerical calculations through a simple API.

Provides secure mathematical computation capabilities including expression evaluation, symbolic math (derivatives, simplification), matrix operations, statistics, and unit conversion, with multi-tier acceleration through WebAssembly and WebWorkers for high-performance calculations.

Enables LLMs to perform accurate mathematical calculations by evaluating expressions using mathjs. Supports basic arithmetic, functions, constants, and complex mathematical operations through natural language requests.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.

An MCP server that automatically optimizes AI prompts using evolutionary algorithms, helping improve prompt performance, creativity, and reliability through iterative testing and refinement.

A Mathematical Computation Protocol server providing 286 mathematical functions across multiple domains with flexible transport options (STDIO/HTTP) and streaming capabilities.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Turns any verb Registry into a real MCP server, where each verb becomes an MCP tool with its own Zod input/output schemas (zero drift).

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

A meta-MCP server that orchestrates tools from multiple MCP servers, enabling complex Python workflows with loops and conditionals.