Integrate Model Context Protocol (MCP) to Enhance AI-Assisted Development

[kubbot]

Background

SurfSense is an AI-powered platform that leverages various LLM technologies to deliver functionality for users. However, the project itself could benefit from AI-assisted development workflows to accelerate its own development and improve contributor experience.

Objective

Implement Model Context Protocol (MCP) integration that allows contributors to use AI assistance throughout the development lifecycle - from code generation to documentation, testing, and debugging - in a standardized way that works well with the project's structure.

Implementation Details

Core Components

1. Setup and Configuration

   • Add MCP configuration files to define project structure for AI tools
   • Create AI-friendly documentation on code organization and patterns
   • Configure project-specific AI prompts that understand SurfSense architecture

2. Development Workflow Integration

   • Implement AI-assisted pull request management
   • Set up AI-powered code review suggestions
   • Create AI-assisted issue triage workflow

3. Specialized AI Assistance

   • Create domain-specific prompts for LLM/RAG components
   • Develop AI templates for common SurfSense extension patterns
   • Build AI-assisted testing workflows

4. Documentation

   • Add guidelines for AI tool usage in the project
   • Document best practices for AI-assisted contributions
   • Create examples of effective AI prompts for SurfSense-specific tasks

Technical Approach

• Leverage SurfSense's existing AI capabilities for internal development
• Integrate with GitHub's new AI-assisted features
• Provide configuration for popular AI coding assistants (GitHub Copilot, Cursor, etc.)
• Ensure AI suggestions follow project conventions and styles

Benefits

• Accelerate onboarding of new contributors with AI-guided introduction to the codebase
• Improve code quality through consistent AI-assisted reviews
• Reduce repetitive coding tasks through well-configured AI assistance
• Make SurfSense's own development showcase the AI-augmented workflows it enables for users

Definition of Done

• MCP configuration is implemented and documented
• AI-assisted workflows are integrated with existing development processes
• Documentation provides clear guidelines for AI tool usage
• Examples demonstrate effective AI-assisted contributions
• Contributor feedback confirms improved development experience

Additional Notes

• This aligns well with SurfSense's AI-focused mission
• Consider creating specific AI prompts for different components (backend, frontend, extension)
• Ensure all AI tooling respects code privacy and security requirements
• Make MCP usage optional but well-supported for contributors who prefer it

This integration will help SurfSense "eat its own dog food" by using AI assistance in its own development, creating a virtuous cycle of improvement in both the product and its development process.

[MODSetter]

Hey @kubbot I am also very interested in making a SurfSense MCP. I plan to work on this soon. I think this https://github.com/tadata-org/fastapi_mcp can really help us.

[cubxxw]

@MODSetter I have seen this project. Do you have any ideas now, such as user stories?

[cubxxw]

In addition to encapsulating the api mcp, I think the capabilities of mcp can be expanded in the project and various mcp clients can be connected. It can ensure that more useful data sources are obtained during the search processing.

[gioandtonic]

I love the proposal and would like to help. ⚠️⚠️⚠️ Just want to point out that the protocol is called Model Context Protocol. ⚠️⚠️⚠️

[MODSetter]

@gioandtonic Thanks for your interest. I am setting up a new ROADMAP. I will pull you in when work on MCP starts.