AI Development Assistant MCP Server is an AI-powered development toolkit designed as a Model Context Protocol (MCP) server for Cursor. It provides intelligent coding assistance through custom AI tools, such as code architect, screenshot analysis, and code review functionalities. Note that this project is primarily a tutorial demo and not production-ready.
This tool is useful for developers who want to enhance their coding workflow with AI-powered features like automated code reviews, generating architectural plans for new features, and analyzing UI screenshots. It's especially beneficial for learning and experimenting with AI-based development tools in a local environment.
Developers, particularly those using Cursor as their editor, can benefit from this tool. It is ideal for individuals interested in exploring AI-driven development practices or those who want to build upon the existing framework to create more advanced tools.
The AI Development Assistant MCP Server is integrated into Cursor via its MCP interface. Users need to configure it under Cursor Settings > Features > MCP by adding the server details, including the path to the built index.js file.
This tool is best used during development workflows where intelligent coding assistance is needed, such as when reviewing code, designing new features, or analyzing UI designs. Since it's a tutorial demo, it is most appropriate for experimentation and educational purposes rather than critical production environments.
To set up the environment, create a 'keys.ts' file in the 'src/env/' directory and add your API keys there. For example, include 'export const OPENAI_API_KEY = "your_key_here";'. Remember, storing API keys in source code is not recommended for production environments.
Yes, contributions are welcome! You can submit a Pull Request with your improvements or fixes. The project is open-source and licensed under the MIT License.
The key features include Code Architect for generating coding plans, Screenshot Buddy for UI design analysis, and Code Review for performing git diff-triggered code reviews.
No, this tool is primarily a tutorial demo and is not intended for production environments. It is designed for learning and experimentation purposes.
You can report issues by opening a ticket with details about what you were trying to do, what happened instead, steps to reproduce the issue, and your environment details. However, note that this is a demo project, so active support may be limited.
MCP (Model Context Protocol) is an open protocol designed to standardize how applications provide context information to large language models (LLMs). Like a 'USB-C port' for AI applications, MCP ensures AI models can seamlessly connect with various data sources and tools.
An MCP Server is a server that supports the MCP protocol, enabling the exchange of contextual information between applications and AI models in a standardized way. It provides developers with an easy way to integrate AI models with databases, APIs, or other data sources.
An MCP Server eliminates the complexity of developing custom adapters by unifying the connection between AI models and various data sources. Whether you're a developer, data scientist, or AI app builder, an MCP Server simplifies the integration process, saving time and resources.
An MCP Server acts as an intermediary bridge, converting contextual information from various data sources into a format that AI models can understand. By adhering to the MCP protocol, it ensures data is transmitted between applications and AI models in a standardized manner.
At mcpserver.shop, you can browse our MCP Server Directory. The directory is categorized by industry (e.g., finance, healthcare, education), and each server comes with detailed descriptions and tags to help you quickly find the option that suits your needs.
The MCP Server Directory on mcpserver.shop is free to browse. However, some servers are hosted by third-party providers and may involve usage fees. Check the detailed page of each server for specific information.
MCP Servers support a wide range of data sources, including databases, APIs, cloud services, and custom tools. The flexibility of the MCP protocol allows it to connect almost any type of data source to AI models.
MCP Servers are primarily designed for developers, data scientists, and AI app builders. However, mcpserver.shop provides detailed documentation and guides to help users of varying technical levels get started easily.
Yes, MCP is an open-source protocol that encourages community participation and collaboration. For more details or to contribute, visit the official MCP documentation.
On mcpserver.shop, each MCP Server’s detailed page includes the provider’s contact information or a link. You can directly reach out to the provider for more details or technical support.