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NN New

MCP Server

Demo MCP server for testing purposes

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Updated Mar 15, 2025

About

NN New is a lightweight demo implementation of an MCP (Model Context Protocol) server, designed to illustrate core concepts and provide a reference for developers experimenting with MCP.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview of the NN‑New MCP Server

The NN‑New server is a lightweight Model Context Protocol (MCP) implementation designed to bridge AI assistants with external data sources and computational tools. It addresses the common pain point of limited contextual awareness in large language models: without direct access to up‑to‑date data or specialized algorithms, assistants can only rely on static knowledge bases. NN‑New solves this by exposing a set of well‑defined resources, tools, prompts, and sampling endpoints that an AI client can query at runtime.

At its core, the server offers a resource registry that catalogues available data endpoints—such as real‑time weather feeds, financial tickers, or internal knowledge graphs. Each resource is accompanied by a concise schema and access controls, allowing developers to expose only the necessary data while preserving privacy. In addition, a tool interface lets clients invoke external functions (e.g., image generation, mathematical solvers, or domain‑specific APIs) with simple JSON payloads. The server’s prompt templates enable the creation of reusable conversational flows, ensuring consistent tone and structure across interactions. Finally, a sampling endpoint provides fine‑grained control over the assistant’s text generation parameters (temperature, top‑k, etc.), giving developers the flexibility to balance creativity and determinism.

These features make NN‑New especially valuable for developers building AI‑powered applications that require real‑time data integration or domain expertise. For instance, a travel assistant can query live flight schedules and then call a booking tool to reserve seats, all within a single conversational turn. A financial analyst chatbot can pull current market data and run predictive models, delivering actionable insights without leaving the chat interface. In educational settings, educators can expose curated content libraries and interactive quizzes, allowing students to explore subjects dynamically.

Integration into existing AI workflows is straightforward: an MCP‑compatible client simply sends a request to the server’s , , or endpoints, receives structured responses, and feeds them into the assistant’s prompt. Because the server adheres to standard MCP schemas, it can be swapped out or extended without modifying client logic. This modularity encourages rapid prototyping and experimentation.

What sets NN‑New apart is its emphasis on clarity and minimalism. By stripping away unnecessary boilerplate, the server delivers a clean API surface that developers can grasp quickly. Its demo‑ready architecture means teams can spin up the server in a matter of minutes and start connecting tools, resources, and prompts—accelerating the journey from idea to production.