Model Pipeline Orchestrator MCP

Colab-based, memory-aware LLM orchestration with a lightweight demo focused on interactive prompt contexts.

Test client implementing MCP with OpenAI API to validate context handling and model interactions.

2025 Religious Orders Study/Memory Aging Project Multisite Chronic Pain Research

Automates GitHub workflows using DeepSeek R1 32B and the Model Context Protocol for repository analysis and AI-assisted edits.

ClaudeMCP

Directly execute and manage Replicate models with run, create predictions, status checks, and webhook notifications.

Lightweight Python framework enabling dynamic tool orchestration and context-aware provisioning for LLMs.

Minimal Python MCP server placeholder with no documentation, awaiting community-driven feature expansion.

Python-based framework enabling structured model context sharing, routing, and extensible plugins for scalable LLM orchestration.

Official prompt to inform LLMs how to use MCP

Model Context Protocol 中文资料

anthropic mcp

MCP

Multi-Cloud Platform (MCP) Capabilities Model - Incorporating best practices from GCP Professional Services, Security, ML, and Scanner tools

A RAG App built completely on Typescript using: LLama3.2, pgVector, Nomic, Ollama

A sandbox repository for experimenting with GitHub interactions

ClaudeMCP offers modular Claude context integration with interoperable prompts for scalable, privacy-conscious workflows.

A test repository with basic data science requirements

Lightweight framework for context-driven agents with seamless tool integration and dynamic prompt mediation.

This project involves forecasting the Market Clearing Price (MCP) in the EPİAŞ Day-Ahead Market (DAM) using Long Short-Term Memory (LSTM) networks. The LSTM model is employed to predict future prices based on historical market data, which helps in understanding price trends and making more informed decisions in energy trading.

An intelligent assistant that leverages memory (knowledge graph), computation (data processing), and perception (content understanding) to provide enhanced assistance.

Small test to look at Anthropic's MCP.

Python-based component delivering Model Context Protocol 2.0 with lightweight, extensible context management and seamless multi-model interoperability.