Python-based prototype enabling efficient model-context exchange with async messaging and pluggable backends.

A primitive, template-driven markdown creator using Claude Desktop, designed for modular, multi-server workflows with developer-focused logging and inspector support.

Lightweight TypeScript chat component with interactive conversations and planned provider-based integration.

Lightweight Python MCP client designed to connect and interact with MCP servers.

Lightweight fetch-oriented adapter enabling remote context retrieval with caching and pluggable backends for seamless data delivery.

Windows-focused setup guide for Claude integration with simple configuration, environment management, and reproducible component orchestration.

Training-focused Model Context Protocol variant designed for business workflows and structured tool usage.

Lightweight TypeScript tool for executing shell commands with structured outputs, Claude Desktop integration, and robust development/debug tooling.

Lightweight Python helper for Model Context Protocol integration, offering quick setup, templated configurations, and debugging aids. It emphasizes practical, developer-friendly workflows by providing sample configurations, streamlined build and publish steps, and seamless Inspector debugging to accelerate integration and testing within local Python projects.

A .NET SDK for MCP enabling type-safe message handling, standardized adapters, and seamless .NET integration to build MCP-powered applications.

Memory-backed context retention with flexible backends, privacy-aware storage, and rapid recall for long-running conversations.

Curated modular toolkit of context-aware Minecraft protocol modules enabling extensible mod interoperability.

Lightweight, extensible tool for exchanging and orchestrating model context across workflows.

A lightweight collection of client libraries enabling seamless MCP server integration with modular adapters.

Lightweight, extensible toolkit for deploying and debugging context-aware flows with streamlined routing and plugin support.

Open-source framework for dynamic AI context with memory, privacy-first controls, and scalable graph-based relationships.

Introductory page showcasing modular context handling for Parker Farm with lightweight farm-focused data flows.

Lightweight Java-based core for context-aware interactions, emphasizing modularity, extensibility, and easy integration with diverse AI providers and data sources.

Lightweight, modular platform enabling dynamic context provisioning and cross-model coordination.

A compact weather data example with per-note storage, custom URI access, and note-summarization tooling for dynamic insights.

Lightweight, extensible client that integrates context into apps, enabling secure sharing, prompt orchestration, and modular, plugin-driven workflows.

Notes-centric MCP offering a custom note:// scheme, summarization prompt, and add-note tool with Claude integration and client notifications.

Go-based MCP server with concurrency-first processing, modular plugins, and easy integration.

Lightweight framework for orchestrating contextual workflows with extensible plugins and smooth integration across tools and models.