UBOS Asset Marketplace: TypeScript MCP Server Template – Powering Intelligent AI Agents

In the rapidly evolving landscape of artificial intelligence, the ability for Large Language Models (LLMs) to access and interact with external data sources is paramount. The Model Context Protocol (MCP) emerges as a critical enabler, standardizing how applications provide context to these LLMs. Within the UBOS Asset Marketplace, we offer a robust and streamlined solution for developers looking to build MCP servers: a simple TypeScript template designed to facilitate the creation of AI-powered tools that seamlessly connect LLMs to your data.

Understanding the Significance of MCP Servers

Before diving into the specifics of our TypeScript template, let’s clarify the role and importance of MCP servers in the modern AI ecosystem. An MCP server acts as a crucial intermediary, bridging the gap between AI models and the vast world of external information. It provides a standardized interface for LLMs to request and receive contextual data, enabling them to perform more sophisticated and informed tasks. Think of it as a translator and data concierge for AI, ensuring it has the right information at the right time.

Without MCP, integrating LLMs with real-world data becomes a complex and often bespoke undertaking. Each integration requires custom code and a deep understanding of the specific data source. MCP simplifies this process, allowing developers to focus on building intelligent applications rather than wrestling with data connectivity.

Introducing the TypeScript MCP Server Template

Our TypeScript MCP Server Template is designed to provide developers with a solid foundation for building MCP servers quickly and efficiently. It’s built with simplicity and ease of use in mind, making it an ideal starting point for both novice and experienced developers. The template leverages the power of TypeScript to provide type safety and enhanced code maintainability.

Key Features:

• Simple Notes API with CRUD Operations: The template includes a basic notes API that demonstrates fundamental CRUD (Create, Read, Update, Delete) operations. This provides a clear example of how to interact with data using the MCP protocol.
• In-Memory Data Storage: For simplicity and ease of setup, the template utilizes in-memory data storage. This means that data is stored in the server’s memory and is not persistent across restarts. This is suitable for development and testing purposes. For production environments, you would typically integrate with a persistent database such as PostgreSQL or MongoDB.
• TypeScript Implementation: The template is written in TypeScript, a superset of JavaScript that adds static typing. This helps to catch errors early in the development process and improves code maintainability.
• JSON Responses: The server returns data in JSON format, a widely used standard for data exchange on the web. This ensures compatibility with a wide range of clients and AI models.
• Ready for Testing with Vitest: The template includes a suite of unit tests written using Vitest, a fast and modern testing framework. This allows you to easily verify the correctness of your code and ensure that it behaves as expected.

Use Cases:

This template is ideal for a variety of use cases, including:

• Prototyping MCP Servers: Quickly create a working prototype of an MCP server to demonstrate its functionality and feasibility.
• Learning MCP Development: Use the template as a learning resource to understand the fundamentals of MCP server development.
• Building Custom MCP Tools: Customize the template to create MCP tools that interact with specific data sources and provide tailored context to LLMs.
• Integrating LLMs with Enterprise Data: Connect LLMs to your organization’s internal data sources to enable more intelligent and data-driven AI applications.
• Developing AI Agents: Develop AI Agents that can access and process real-world information through MCP servers, enabling them to perform complex tasks and make informed decisions.

Getting Started with the Template

Setting up and running the TypeScript MCP Server Template is straightforward. Follow these simple steps:

1. Installation: Clone the repository and install the necessary dependencies using npm install.
2. Running the Server: Start the development server using npm run dev. This will launch the server and make it accessible on a specified port (typically port 3000).
3. Building for Production: To prepare the server for deployment, run npm run build followed by npm start. This will create a production-ready build of the server.

Available Tools

The template includes a set of pre-built MCP tools that demonstrate basic CRUD operations on notes. These tools can be accessed via HTTP requests to the server:

• getNote: Retrieves a note by its ID.
• getAllNotes: Retrieves all notes.
• createNote: Creates a new note.
• updateNote: Updates an existing note.
• deleteNote: Deletes a note by its ID.

These tools serve as a starting point for building more complex and specialized MCP tools that cater to your specific needs.

Testing and Customization

The template includes a comprehensive suite of unit tests that you can run using npm test or npm run test:watch for continuous testing. These tests help ensure the stability and correctness of your code.

Customizing the template is easy. Simply modify the tools in src/server.ts to interact with your desired data sources and provide the specific context that your LLMs require. You can also add new tools and functionalities to extend the server’s capabilities.

UBOS: Your Full-Stack AI Agent Development Platform

The TypeScript MCP Server Template is a valuable asset within the broader UBOS ecosystem. UBOS is a full-stack AI Agent Development Platform designed to empower businesses to orchestrate AI Agents, connect them with enterprise data, and build custom AI Agents with their own LLM models and Multi-Agent Systems.

How UBOS Complements the MCP Server Template

• Seamless Integration: The MCP Server Template provides a standardized way to connect your AI Agents, built on UBOS, with external data sources. This allows your agents to access and process real-world information, enhancing their intelligence and decision-making capabilities.
• Simplified Data Access: UBOS simplifies the process of connecting your AI Agents with enterprise data. By leveraging MCP servers, you can ensure that your agents have access to the right data at the right time, without the need for complex custom integrations.
• Enhanced Agent Capabilities: By connecting your AI Agents to external data sources through MCP servers, you can unlock a wide range of new capabilities. Your agents can now perform tasks such as:
  • Real-time Data Analysis: Analyze real-time data streams to identify trends and patterns.
  • Personalized Recommendations: Provide personalized recommendations based on user data and preferences.
  • Automated Decision-Making: Automate decision-making processes based on real-world data and predefined rules.
  • Proactive Problem Solving: Proactively identify and solve problems by monitoring data and triggering appropriate actions.

Benefits of Using UBOS for AI Agent Development

• Rapid Development: UBOS provides a comprehensive set of tools and frameworks that accelerate the development of AI Agents.
• Scalability: UBOS is designed to scale to meet the demands of enterprise-level AI deployments.
• Security: UBOS incorporates robust security measures to protect your data and AI Agents from unauthorized access.
• Flexibility: UBOS supports a wide range of LLMs and data sources, giving you the flexibility to choose the technologies that best fit your needs.

Conclusion

The TypeScript MCP Server Template is a powerful tool for developers looking to build AI-powered applications that leverage the power of LLMs. By providing a standardized interface for accessing external data, MCP enables AI models to perform more sophisticated and informed tasks. Combined with the UBOS platform, this template provides a complete solution for developing and deploying intelligent AI Agents that can transform your business.

Start building your own MCP servers today and unlock the full potential of AI!