# Context Management

An MCP server for expanding the context window/memory of AI agents, supporting storage, retrieval, and management of memories, including semantic search functionality.

The MCP context manager is a solution for achieving cross - session persistent AI context through a knowledge graph, supporting multi - domain intelligent management.

The MCP Server is a lightweight system for managing contextual data of AI models to enhance the response capabilities of AI applications.

An MCP server implementation based on Gemini, providing powerful context management and caching functions, supporting a context window of up to 2 million tokens, and suitable for integration with various AI clients.

This project demonstrates how to integrate Claude AI into the development process through the MCP protocol, including an MCP server and a to-do application demonstration to achieve AI-assisted software development.

An MCP server for extending the context window/memory of AI agents, supporting the storage, retrieval, and management of memory content, including semantic search functionality.

Model Context Protocol Server Project

The MCP Cobot Server is an implementation of the server based on FastMCP, designed specifically for the M5 MyCobot280 collaborative robot, implementing the MCP standard for efficient context management.

An MCP service for code analysis based on tree-sitter, providing intelligent code context management capabilities for Claude.

This project implements the Model Context Protocol (MCP) framework for dynamic management of query routing and execution context, supporting climate data analysis.

Popmelt MCP is a framework that enables in - depth personalized AI interactions through multi - dimensional user preferences, including core components such as style vectors, context weighting, and a dynamic design system.

A model context protocol SDK implemented in TypeScript, providing client - side and server - side functions for integration with LLMs.

The Memory Journal MCP Server is a project context management tool for AI-assisted development, solving the problem of AI context loss across multiple threads and sessions through persistent knowledge graphs and intelligent context recall.

This project is an MCP service based on Apache Unomi, enabling Claude to maintain context through user profile management, providing functions such as profile lookup, attribute management, and session handling.

A model context protocol SDK implemented in TypeScript, supporting client and server functions for integration with LLMs.

The MCP plugin of ElizaOS implements the integration with the Model Context Protocol (MCP), enabling agents to connect to multiple MCP servers and obtain resource, prompt, and tool support.

The MCP Python SDK is a Python development toolkit that implements the Model Context Protocol (MCP), allowing developers to build standardized MCP servers and clients to provide context data, tools, and interaction templates for LLM applications.

This project implements a personal context management server based on the MCP protocol, which is used to store and update users' personalized data, enabling AI assistants to maintain memory across sessions and provide personalized services.

An intelligent text summarization MCP server designed for AI workflows, providing intelligent summarization functions for command output, file content, and directory structure, and optimizing the context window management of AI agents.

A Node.js-based Cardano blockchain integration service that provides tool registration, knowledge base management, and context processing functions.

An AI planning system integrating Google Gemini CLI and Claude Code, providing functions such as automatic planning and execution, persistent context management, and MCP integration.

The Model Context Protocol (MCP) SDK implemented in TypeScript, providing client and server functions for standardizing LLM context interactions.

The SlimContext MCP server is an AI chat history compression tool based on the SlimContext library, providing two compression strategies for clients through the Model Context Protocol: token - based trimming compression and AI - driven intelligent summary compression.

The MCP server implemented by the VS Code extension provides a standardized context interaction protocol for AI assistants and supports the seamless integration of the development environment and LLMs.

A smart context management MCP server for context tracking, recovery, and project management in AI development sessions, avoiding the loss of conversation context due to token limitations.

A context management and caching MCP server based on Gemini, supporting a large context window of 2M tokens and providing session management and API caching functions.

A model context protocol (MCP) SDK implemented in Python for building standard servers and clients interacting with LLMs

An intelligent text summarization MCP server designed for AI workflows, providing intelligent summarization functions for command output, file content, and directory structure

Memory Bank MCP is a server based on the Model Context Protocol (MCP) for managing Memory Banks, allowing AI assistants to store and retrieve information across sessions. It supports remote SSH server storage, provides multiple operating modes and tools to help AI assistants maintain context and track cross - session progress.

An MCP server for persisting development memory across projects, automatically capturing and organizing development context, code changes, and user interactions. Currently, it is hindered by file system access and JSON response handling issues.