# Model protocol

Upsonic is a reliability - focused framework aiming to achieve trustworthy agent workflows within an organization through advanced reliability features such as a validation layer, triangular architecture, validation agents, and an output evaluation system. It addresses key challenges such as reliability, Model Context Protocol (MCP), integrated browser and computer usage, and secure runtime.

The MCP server project of Satellite, which implements the Model Context Protocol specification, is used for handling model interactions, providing functions for data product retrieval and invocation, supporting TypeScript and Zod validation, and requiring API key authentication.

An example of implementing a Java MCP service with Spring AI, supporting Spring Boot 3.4.x or higher

mcpo-docker is a Docker image project that provides OpenAPI-compatible HTTP endpoints for MCP (Model Context Protocol) servers, facilitating integration with OpenWebUI.

A proof - of - concept implementation of MCP Server that provides tools for accessing and operating Loomers, forms, form responses, and project data.

A Node.js-based custom prompt server for the Claude AI model, supporting modular classification management and chained prompt execution.

The MCP server is a model context protocol service based on HTTP and SSE, providing guidelines for cloning, building, and running, and supporting debugging and connection functions.

This project demonstrates a serverless MCP (Model Context Protocol) tool implementation based on AWS Lambda, including a Python server - side and a TypeScript client, supporting streaming HTTP communication. The server - side simplifies the MCP tool development process, has built - in session state management, and demonstrates integration with Amazon Bedrock.

DVMCP is an educational project that demonstrates security vulnerabilities by deliberately implementing a vulnerable Model Context Protocol (MCP). It contains 10 challenges of increasing difficulty to help learn about security issues in MCP implementations.

MCP MindMesh is a server that manages multiple Claude 3.7 Sonnet instances, achieving multi - agent collaboration through quantum - inspired swarm intelligence and generating highly consistent responses.

The Superface MCP Server is a project that provides Superface tool services through the Model Context Protocol (MCP).

The Revit MCP server is a TypeScript - based bridge service that enables real - time model data interaction between Claude AI and Autodesk Revit

mcp - client - browser is a TypeScript library that provides MCP (Model Control Protocol) support for browsers, enabling seamless interaction with large language models.

Gitlab MCP Server is an open - source service based on the Model Context Protocol, inherited from the MCP server on Github.

The OpenAPI MCP Server is a model context protocol service for Claude/Cursor that supports searching and exploring OpenAPI specifications through oapis.org. It helps users obtain the identifiers of APIs, summaries described in simple language, and detailed information about endpoints through a three-step process. It is suitable for API exploration and code generation.

Service projects using Trusted Advisor as the model context protocol

The MCP service of ResilientDB provides a blockchain read - write interface for large language models

This project enables large language models to directly understand and generate audio effect modules in the Max audio processing software through the Model Context Protocol (MCP). It supports explaining, modifying, and creating audio effect modules and provides an interaction interface with LLMs.

MCP OpenVision is an image analysis server based on OpenRouter's vision models, providing image analysis capabilities for AI assistants.

Ollama MCP Server is a protocol server that connects local Ollama LLM models with MCP - compatible applications, providing functions such as model management and conversation interaction.

Custom MCP (Model Context Protocol) server project

A Python-based Solana blockchain model context protocol server that provides real-time data processing, model interaction interfaces, and RESTful APIs, and supports Docker deployment.

The Perplexity AI MCP Server project provides standardized interfaces to access the functions of Perplexity AI, including chatting, searching, and document retrieval.

The official implementation of Supavec's MCP server, used to obtain relevant content from Supavec.

A lightweight MCP server implementation that provides access to OpenAI o3 models and other models through the Poe API, supporting the selection of different models via command-line flags.