Bitbucket integration for the Model Context Protocol.

GitHub API integration offering search, details, contents, and issue management with streamlined automation and developer-friendly tooling.

Compact protocol-driven mind map generator with CLI setup and rapid prompt-to-map conversion.

A multi-source integration demo showcasing quick access to code snippets, DB ops, design assets, and repo tasks via Cursor IDE.

Working with MCP (Model Context Protocol)

Modular framework enabling context-aware orchestration with pluggable adapters, optimized routing, and policy enforcement to differentiate it from other implementations.

Lightweight Python implementation enabling rapid Model Context Protocol interactions with asynchronous I/O and plugin support.

Flexible Model Context Protocol integration to read Datagroom data and empower LLM-driven reasoning with dataset metadata.

Akademische Fallstudie zur kontextbasierten Anbindung externer Werkzeuge in KI-Anwendungen, mit zweistufigem Architekturkonzept.

TypeScript implementation enabling modular context provisioning and request routing via Model Context Protocol.

Lightweight Python framework with FastAPI backend, offline AI, and modular GUI for device discovery and dashboard generation.

Model Context Protocol for Arxiv

Modular MCP server enabling easy tool registration, retrieval, and configurable tool metadata for Python projects.

Dynamic tool invocation and context-aware planning for intelligent, multi-agent workflows with OpenAI integration.

Next.js sample with Vercel adapter, SSE transport, Redis streaming, and Fluid compute optimization for scalable context handling.

Lightweight FastAPI-based context coordination for AI models with pluggable memory, secure access, and modular integration. It enables memory and tool sharing across agents, clean separation of concerns, and simple deployment for modern AI workflows. Onboarding is quick for teams adopting protocol patterns.

CLI-driven interactive chat with document-aware prompts and extensible tool integrations, designed for rapid experimentation and customization.

CLI-driven AI chat with document retrieval and extensible tool integrations via a modular protocol.

Two-context demo with journey and news domains, configurable OpenAI backend via env vars, using ports 8000 and 8001.

Automatic parsing and Markdown documentation with parameter details, code quality insights, and comment preservation.

A Python-based demonstration of context handling with clear tooling interactions and extensible patterns.

Lightweight Python-based orchestration with memory and tools for coherent interactions across tasks

Python-first hub enabling modular adapters and standardized context sharing across projects.

A modular host-client-server framework coordinating AI resources through JSON-RPC, enabling specialized, external service integration and dynamic resource orchestration.