NextChat with MCP Server Builder
by vredrick2
This is a customized version of NextChat that allows users to create and deploy MCP (Model Context Protocol) servers through chat interactions, leveraging OpenRouter for LLM models. It simplifies the process of building and deploying AI-powered tools.
Last updated: N/A
What is NextChat with MCP Server Builder?
NextChat with MCP Server Builder is a modified version of NextChat that enables the creation and deployment of Model Context Protocol (MCP) servers through a chat interface. It uses OpenRouter to access a variety of LLM models, allowing users to easily build and deploy custom AI tools.
How to use NextChat with MCP Server Builder?
To use this, clone the repository, install dependencies, configure the .env.local file with your OpenRouter API key, and start the development server. Then, initiate a new chat and use phrases like 'Create an MCP server' to start the server creation process, following the prompts to define the server's functionality. The system will then extract tools and provide integration instructions.
Key features of NextChat with MCP Server Builder
Chat-based MCP Server Creation
Automatic Tool Extraction
One-click Deployment (simulated)
Integration Guides for various AI systems
OpenRouter Integration
Use cases of NextChat with MCP Server Builder
Creating custom AI tools for specific tasks
Building and deploying AI-powered APIs
Integrating AI functionalities into existing applications
Rapid prototyping of AI-driven services
FAQ from NextChat with MCP Server Builder
What is an MCP server?
What is an MCP server?
An MCP (Model Context Protocol) server provides a standardized way to interact with AI models and tools, allowing them to be easily integrated into different applications.
What is OpenRouter?
What is OpenRouter?
OpenRouter is a service that provides access to a wide range of LLM models through a single API key.
How does the tool extraction work?
How does the tool extraction work?
The system uses pattern matching to identify keywords in the user's description that indicate specific tool types, such as calculator or translation tools.
Is the deployment real?
Is the deployment real?
The current implementation simulates deployment with mock URLs. A production environment would connect to a real deployment service.
Can I use other LLMs besides the default one?
Can I use other LLMs besides the default one?
Yes, you can change the DEFAULT_MODEL and CUSTOM_MODELS variables in the .env.local file to use other models available through OpenRouter.