#models

A Model Context Protocol (MCP) server that provides tools to query Erick Wendel's contributions across different platforms

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Triplewhale MCP Server

Model Context Protocol (MCP) Server for Rust

A comprehensive collection of Model Context Protocol (MCP) servers

Dataset search and model metadata management tools.

Collection of MCP Servers ofr use with anthropic and other models

Desktop application for managing Model Context Protocol servers (MCP). Provides a centralized interface to configure and manage MCP servers for use with LLMs and AI assistants such as Claude.

This MCP server was developed to improve Cline's agentic workflows by being up-to-date with the public repositories and docs under

Python wrapper for seamless integration with different MCP-servers and open-source large language models (LLMs).

Awesome MCP Servers - A curated list of Model Context Protocol servers

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Cohere MCP Server

(Demo) MCP Server to create and draw .vox models file locally

A Model Context Protocol (MCP) server that integrates large language models (LLMs) with quantum computing platforms, such as IBM Quantum’s Qiskit.

Monorepo for Sylph Lab Model Context Protocol (MCP) tools and servers.

Vibe querying with MCP server for Azure Data Explorer (Kusto)

A model that uses streamlit as frontend and MCP server(notion and postgres tools) and FAST API for integration

OmniMind: An open-source Python library for effortless MCP (Model Context Protocol) integration, AI Agents, AI workflows, and AI Automations. Plug & Play AI Tools for MCP Servers and Clients, powered by Google Gemini.

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A Nuclei security scanning server based on MCP (Model Control Protocol), providing convenient vulnerability scanning services.一个基于 MCP (Model Control Protocol) 的 Nuclei 安全扫描服务器，提供便捷的漏洞扫描服务。

Things related to artificial intelligence built on top of Nasdanika capabilities

MCP server to persist chat artefacts and rules

Monorepo for Sylph Lab Model Context Protocol (MCP) tools and servers.

A Minecraft MCP Server powered by Mineflayer API. It allows to control a Minecraft character in real-time, allowing AI assistants to build structures, explore the world, and interact with the game environment through natural language instruction

An LLM-based smart terminal for lazy guys :P

A lightweight large language model input-output tracker—launch with a single command, integrate effortlessly.

MockLoop MCP is a powerful tool that helps developers create mock API servers effortlessly. 🚀 With just a few commands, you can set up a testing environment that mimics your production API. 💻

CodeCompass: AI-powered Vibe Coding with MCP. Connects Git repositories to AI assistants like Claude, using Ollama for privacy or OpenAI for cloud. Integrates with VSCode, Cursor, and more.

This repository provides an implementation of a Model Context Protocol (MCP) server for AWS S3, enabling AI models, particularly Large Language Models (LLMs), to securely interact with S3 buckets. The server offers a standardized interface to list S3 buckets, list objects within buckets, and download file contents.

rival-mcp MCP server for querying AI model comparison data from rival.tips This server lets AI coding assistants — Claude Code, Cursor, Windsurf, and any MCP-compatible client — natively query model benchmarks, pricing, capabilities, and side-by-side comparisons without leaving your editor. Quick Start npx rival-mcp No API key required. All data is served from the public rival.tips API. Configuration Claude Code Add to your .claude/settings.json (project-level) or ~/.claude/settings.json (global): { "mcpServers": { "rival": { "command": "npx", "args": ["-y", "rival-mcp"] } } } Claude Desktop Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows): { "mcpServers": { "rival": { "command": "npx", "args": ["-y", "rival-mcp"] } } } Cursor Add to your Cursor MCP settings (.cursor/mcp.json): { "mcpServers": { "rival": { "command": "npx", "args": ["-y", "rival-mcp"] } } } Windsurf Add to your Windsurf MCP config: { "mcpServers": { "rival": { "command": "npx", "args": ["-y", "rival-mcp"] } } } Available Tools list-models List all AI models with optional filtering. Parameters: Parameter Type Description provider string (optional) Filter by provider: OpenAI, Anthropic, Google, Meta, Mistral, etc. category string (optional) Filter by category: flagship, reasoning, coding, small, free, image-gen capability string (optional) Filter by capability: chat, code, vision, image-gen, function-calling q string (optional) Free-text search across name, ID, provider, and description Example prompts: "List all Anthropic models" "Show me free models" "What models support vision?" get-model Get detailed information about a specific model — benchmarks, pricing, capabilities, unique features, and provider availability. Parameters: Parameter Type Description id string (required) Model ID, e.g. gpt-4.1, claude-3.7-sonnet, gemini-2.5-pro Example prompts: "Get details on claude-3.7-sonnet" "What are the benchmarks for gpt-4.1?" compare-models Compare 2-3 models side by side — benchmarks, pricing, capabilities, and shared challenges. Parameters: Parameter Type Description models string (required) Comma-separated model IDs (2-3). Example: gpt-4.1,claude-3.7-sonnet Example prompts: "Compare GPT-4.1 vs Claude 3.7 Sonnet" "How does Gemini 2.5 Pro stack up against GPT-4.1 and Claude Sonnet?" search-models Search for models by name, description, or capability when you don't know the exact model ID. Parameters: Parameter Type Description query string (required) Search query, e.g. vision, cheap coding, fast reasoning Example prompts: "Find models good at coding" "Search for cheap reasoning models" Development # Install dependencies npm install # Run in development mode npm run dev # Build for production npm run build # Run the built server npm start How It Works This MCP server communicates over stdio (standard input/output) using the Model Context Protocol. When an AI assistant needs model comparison data, it calls the appropriate tool, which fetches data from the rival.tips public API and returns structured JSON. The server exposes no resources or prompts — only tools. All data is read-only and publicly available. Data Source All model data comes from rival.tips, an AI model comparison platform featuring: 60+ AI models with benchmarks, pricing, and capability data Side-by-side comparisons with shared challenge responses Community-driven AI duel voting and rankings Pre-generated showcase responses across coding, creative, and reasoning tasks License MIT

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AI workspace platform that provides unified access to multiple frontier AI models, assistants with persistent memory, and integrated tools for web search, document analysis, code creation, and data visualization. Features team collaboration capabilities, screen sharing for context, voice interaction, and MCP integrations for connecting external apps and services. Designed for individuals, teams, enterprises, and educational institutions who want to avoid vendor lock-in while maintaining secure, collaborative AI workflows across different models and tools.

A MCP server that integrates with ModelScope's ecosystem, providing seamless access to AI models, datasets, apps, papers, and generation capabilities through popular MCP clients.

Intelligent Model Context Protocol (MCP) server for AI-assisted API development. Generate mock servers from OpenAPI specs with advanced logging, performance analytics, and server discovery. Optimized for AI development workflows with comprehensive testing insights and automated analysis.

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