Introduction

Meet Sekora Document Search MCP - our specialized server that brings intelligent document search capabilities to AI assistants. Built with TypeScript and designed for extensibility, this MCP server enables seamless document discovery and content retrieval across multiple sources.

📦 Available on NPM: @sekora/document-search-mcp

What is Document Search MCP?

The Sekora Document Search MCP is a TypeScript-based server that connects AI assistants to your document repositories. Currently featuring robust Google Drive integration, it’s architected to support multiple document sources as we expand the platform.

Core Features

🔍 Multi-Source Document Search

  • Google Drive Integration: Complete OAuth 2.0 authenticated access
  • Full Content Retrieval: Extract and analyze document contents
  • Extensible Architecture: Built to support additional document sources

🛡️ Type-Safe Development

  • TypeScript Foundation: Fully typed for reliability and maintainability
  • Zod Validation: Runtime type checking and validation
  • Modern Architecture: Built on the MCP Framework

🚀 Developer-Friendly Tools

The server provides four essential tools for document operations:

  • setup_google_drive: Configure Google Drive authentication
  • search_documents: Find documents across connected sources
  • get_document_content: Retrieve full document content
  • list_sources: View all configured document sources

Technical Architecture

Requirements

  • Node.js: 18.0.0+
  • OAuth 2.0: Google Drive authentication
  • TypeScript: Full type safety throughout

Modular Design

The project follows a clean, modular architecture:

  • Connector Pattern: Extensible design for multiple document sources
  • Type-Safe Operations: Leveraging TypeScript and Zod for reliability
  • MCP Framework: Built on the Model Context Protocol standard

Use Cases

Research Teams

  • Quickly find relevant documents across Google Drive
  • Extract content for analysis and synthesis
  • Maintain organized document workflows

Content Creators

  • Search through extensive document libraries
  • Access historical content for reference
  • Streamline content research processes

Business Users

  • Locate important documents instantly
  • Access document content through natural language
  • Integrate document search into AI workflows

Getting Started

Installation

npm install @sekora/document-search-mcp

Development Commands

# Build the project
npm run build

# Start development server
npm run dev

# Run tests
npm test

Configuration

Set up Google Drive integration through OAuth 2.0 authentication using the setup_google_drive tool.

Development Workflow

The project includes comprehensive development tooling:

  • Build System: Modern TypeScript compilation
  • Development Server: Hot reload for rapid iteration
  • Testing Suite: Comprehensive test coverage
  • Type Checking: Full TypeScript validation

Extensibility

While initially focused on Google Drive, the architecture supports easy addition of new document sources:

  • Connector Interface: Standardized approach for new integrations
  • Type-Safe Extensions: All new connectors benefit from TypeScript safety
  • Modular Design: Add sources without affecting existing functionality

Project Status

🚧 Active Development: Continuous feature additions and improvements
✅ Google Drive Ready: Full OAuth 2.0 integration complete
✅ Type-Safe: Complete TypeScript implementation
✅ Open Source: MIT Licensed with community contributions welcome

Repository

Explore the complete source code: sekora-ai/sekora-document-search-mcp

Roadmap

Upcoming Features

  • Microsoft OneDrive: Enterprise document access
  • Dropbox Integration: Cloud storage document search
  • Local File System: Search local document repositories
  • Advanced Filtering: Enhanced search capabilities with metadata filtering

Enhanced Capabilities

  • Document Indexing: Improved search performance
  • Content Analysis: AI-powered document insights
  • Batch Operations: Bulk document processing

Contributing

We welcome contributions from the community! Whether it’s:

  • Adding new document source connectors
  • Improving search algorithms
  • Enhancing type safety
  • Writing documentation

Check out our GitLab repository to get started.

Conclusion

The Sekora Document Search MCP represents our vision for intelligent document discovery in the age of AI assistants. By providing type-safe, extensible, and powerful document search capabilities, we’re making it easier than ever to connect AI with your document repositories.

Stay tuned as we continue expanding support for additional document sources and enhanced search capabilities!

Ready to integrate document search into your AI workflow? Visit our repository to get started!