Lightweight, modular framework for managing model context, prompts, and tool integrations with extensible plugins.

Notebook-driven neuron-level MCP server showcasing modular components and context-aware routing.

Modular, extensible context-sharing framework enabling secure cross-agent collaboration with plugin support and versioned schemas to ensure interoperability across diverse tools and runtimes.

Lightweight, Java-based context management tool with pluggable adapters, modular architecture, and robust lifecycle for scalable AI integrations.

Lightweight Python-based MCP 2.0.4 server enabling structured model context exchanges with pluggable adapters and fast deployment.

Lightweight Python-based context management with dynamic prompts and pluggable adapters for cross-model workflows and extensible tooling.

Lightweight, extensible Python implementation of MCP 2.5 with pluggable adapters and context management.

Dynamic context routing with policy-driven interactions, modular architecture, and plugin integration for scalable AI workflows in 2.5.

Context-aware orchestration with modular prompts, retrieval integration, and secure plugin extensions for flexible, governed deployments.

Event-driven trigger server shaping adaptive model-context interactions via external signals.

Lightweight C++ runtime focused on integer exceptions and simple memory wrappers for bare-metal and low-end devices.

High-performance, protocol-first solution for scalable context-aware model hosting and orchestration.

Lightweight Python implementation enabling modular context routing with extensible adapters.

A modular, Python-based MCP server delivering context-aware routing, plugin extensibility, and production-ready features for scalable LLM workflows.

Python-based Mocopi data sender enabling direct local delivery and internet transmission via MCP.

Lightweight, extensible MSP 2.5 server in Python enabling modular model context exchange.

Placeholder for a modular model-context foundation prioritizing flexible context handling and AI workflow integration in Python.

Lightweight Java agent enabling context-aware tool orchestration with pluggable integrations and asynchronous messaging for scalable deployments.

Python-based, modular implementation of the Model Context Protocol 2.5.5 featuring extensible context handling, dynamic tool support, and lightweight, production-ready orchestration.

Python-based 2.0 protocol implementation with modular plugins and lightweight context handling for scalable cross-agent coordination.

Minimal Python MCP 2.5.1 server with context handling and extensibility.

Lightweight, plugin-driven MCP 2.5 with efficient context exchange and secure session management for AI tooling.

Lightweight Python-based implementation of Model Context Protocol 2.0 with extensible plugins and interoperable context sharing.

Lightweight Python MCP server enabling context-aware routing and multi-model integration with pluggable providers.