An audio transcription MCP service based on MLX Whisper, supporting transcription of local files, Base64 audio, and YouTube videos, optimized for Apple M-series chips.

A server project based on the Model Context Protocol (MCP) that provides access to baseball statistical data through the MLB Stats API and the pybaseball library, including data sources such as Statcast, Fangraphs, and Baseball Reference, and supports data visualization.

The MCP server of MLflow Prompt Registry enables access to and management of prompt templates from MLflow.

An MCP service implementation based on the Balldontlie API, providing query functions for player, team, and game information in the NBA, NFL, and MLB.

A Python - based ML model provenance management service built with FastAPI and SQLAlchemy, providing functions such as dataset management, entity tracking, activity logging, proxy management, and provenance relationship tracking.

PromptLab is an intelligent system that optimizes basic user queries into AI system prompts through MLflow integration, providing dynamic template matching and parameter extraction functions.

A server project compatible with the MCP protocol, providing atomic-scale simulation functions through ASE, pymatgen, and machine learning interatomic potentials (MLIPs). It is currently under active development.

This project provides a natural language interaction interface for MLflow through the Model Context Protocol (MCP), allowing users to query and manage machine learning experiments and models in English. It includes server - side and client - side components.

An MCP server that provides access to the BALLDONTLIE sports data API, covering more than 200 data endpoints across 15 major sports leagues, including the NBA, WNBA, NFL, MLB, etc., with comprehensive information on teams, players, games, statistics, odds, etc.

OneCite is a powerful academic citation tool that can automatically convert messy references (such as DOI, title, arXiv ID, etc.) into citation entries with standard formats and complete data. It supports multiple formats such as BibTeX, APA, MLA, and provides command - line, Python library, and AI assistant integration.

This project provides MCP protocol support services for the MLflow Prompt Registry, enabling the functions of retrieving and managing prompt templates from MLflow, and is mainly used for conveniently invoking preset prompts in Claude Desktop.

This project provides a Model Context Protocol (MCP) service for MLflow through a natural language interface, simplifying the management and query of machine learning experiments and models.

An MLB data service based on the MCP protocol, providing comprehensive access to baseball statistical data, including team standings, schedules, player information, etc., and supporting AI application integration.

Implementation of the MCP service for the MLflow Prompt Registry, supporting the retrieval and management of prompt templates from MLflow, facilitating users to quickly invoke preset workflows in Claude Desktop.

The Cloudera ML Model Control Protocol (MCP) is a Python toolkit that provides functions for integrating with the Cloudera Machine Learning platform, including services such as file management, job scheduling, model management, and experiment tracking.

MCP Servers is a collection of servers and services for a Model Composition Platform (MCP), aiming to promote the integration and deployment of various AI/ML models and services. The project adopts a modular architecture, supporting standardized communication and scalable design, and includes various server types such as weather services.

A document search assistant integrated with Claude AI. It enhances Claude's document retrieval capabilities through the MCP server and supports intelligent search and explanation of documents for multiple AI/ML libraries.

This project provides interaction functions for MLflow through a natural language interface. It includes server - side and client - side components, supports querying experiments, model registration, and system information, and simplifies MLflow management operations.

An MLB data API encapsulation service based on the MCP framework, providing functions such as schedule query, game result query, team information query, and player query.

Project summary

This is an MCP server based on FastAPI, providing baseball data query functions from MLB and Fangraphs through the pybaseball library, including player data, team statistics, and league leaderboards.

A secure MCP server implementation for executing controlled command-line operations, providing comprehensive security features, including command whitelisting, path validation, and execution control.

An MCP server project that enhances the document search capabilities of Claude AI, supports multi-AI/ML library document search, and integrates Claude reasoning capabilities and intelligent web search.

The mcp-server-suite is an open-source collection of MCP servers, aiming to become the 'HuggingFace' in the field of automation. It provides modular server components, supporting various functions from web searches to database operations, and encourages community contributions for expansion. The project includes core servers and various planned professional services, covering AI/ML, software development, and non-technical scenarios. The goal is to simplify the automation process through a standardized protocol.

Implementation of the HANA Cloud MCP Server, providing model context protocol services