"Providing Mathematical and Scientific Calculation Functions for a Single-Modal LLM" matching MCP servers:

A stateless MCP server that exposes arithmetic operations (add, subtract, multiply, divide) as tools over HTTP, enabling AI assistants to perform basic calculations conversationally.

Connects AI agents to Modal.com infrastructure, allowing management of deployments, apps, containers, volumes, secrets, and environments via MCP tools.

Provides real-time access to over 200 million scientific papers and full-text extraction from major academic sources including arXiv, OpenAlex, and PubMed Central. It enables users to search, fetch metadata, and analyze citations across multiple research disciplines through a unified Model Context Protocol interface.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

The MCP protocol server based on JSXGraph provides 13 mathematical visualization tools suitable for educational mathematics, engineering, and scientific applications.

Provides intelligent summarization capabilities through a clean, extensible architecture. Mainly built for solving AI agents issues on big repositories, where large files can eat up the context window.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.

MCP server toolkit with payload library, WAF bypass generator, rate limiter, plugin system, and inter-MCP bridge for security testing.

Enables importing AI provider usage CSVs or syncing OpenRouter/OpenAI costs into a local SQLite ledger, then querying spend, budgets, and invoice-style summaries via MCP tools.

MCP server for reviewing code changes using LLMs, supporting Copilot, Ollama, and OpenAI-compatible endpoints.

MCP server for managing a project backlog as Markdown files in Git, enabling AI agents to read, create, and update tasks programmatically.

Builds a local, citation-aware wiki from an approved project scope and exposes it as an MCP server with a single read-only tool for agents to explore the wiki.

MCP server that completes prompts with automatic provider fallback across OpenAI, Anthropic Claude, and Google Gemini. It is rate-limit aware, retries on transient failures, and provides a transparent attempt log.

An MCP server that provides local, private, synchronous access to Ollama models for prompt answering, text classification, and model listing, without any file access or command execution.

Give your AI assistant real-time LLM/VLM knowledge. Pricing, benchmarks, and recommendations — updated every hour, not every training cycle.

Enables an LLM to autonomously maintain a Markdown-based wiki with YAML frontmatter, using hybrid BM25 and local CPU vector search for fully offline retrieval without external APIs or databases.

MCP chess runtime that lets LLMs play, analyze, and adapt strength by exposing Stockfish, human move likelihood (Maia3), and Lichess statistics, with the LLM handling strategy and the server handling computation.

Centralized encrypted gateway that routes requests to 11+ LLM providers (API keys and CLI subscriptions) through a single OpenAI-compatible endpoint, with MCP tools for vault operations, code search, and shared state.

Enables AI coding agents to run multi-model council deliberations by concurrently querying OpenAI and DeepSeek for architectural planning and adversarial critique, then synthesizing the results into actionable implementation decisions.