VeriTeknik

Building Model-Agnostic AI Infrastructure

🎯 What We Do

VeriTeknik develops plugged.in - a model-agnostic platform that gives any AI system unified access to:

• 📚 Knowledge - RAG-powered document libraries with contextual AI
• 🧠 Memory - Persistent context and conversation history across sessions
• 🔧 Tools - Universal MCP (Model Context Protocol) server management

Whether you use Claude, ChatGPT, Gemini, or any other AI model, plugged.in works seamlessly with all of them.

🎥 Watch Plugged In Demo

Click the thumbnail above to see plugged.in in action!

🌟 The Plugged.in Ecosystem

Note: Dashed lines in the ecosystem graph below represent features currently under development.

pluggedin-app

One Platform. All AI Models. Unlimited Possibilities.

The central hub for managing Knowledge, Memory, and Tools across any AI model. Connect your favorite AI to your data, context, and capabilities without vendor lock-in.

• Technology: TypeScript, Next.js, PostgreSQL
• Core Features:
  • Universal RAG for any AI model
  • Cross-model memory and context
  • MCP server orchestration
  • Social sharing and collaboration
• License: AGPL-3.0
• 

pluggedin-mcp-proxy

One MCP Connection. Infinite Tool Access.

The intelligent proxy that manages all your MCP servers through a single connection, compatible with any MCP-enabled AI client.

• Technology: TypeScript
• Key Benefits: Unified tool management, seamless integration, model-agnostic architecture
• License: Apache-2.0
• 

MCP Registry

A community driven registry service for MCP servers.

Discover and share MCP servers with the community. Our registry provides a centralized hub for finding and publishing MCP server implementations.

• Technology: TypeScript
• License: Apache-2.0
• 

🛠️ SDKs & Developer Tools

Integrate plugged.in capabilities into your applications with our official SDKs supporting Javascript, Go, and Python:

Plugged.inKit JS

• JavaScript/TypeScript SDK for Node.js and browser environments
• 

Plugged.inKit Go

• Go SDK for high-performance server applications
• 

Plugged.inKit Python

• Python SDK for AI/ML workflows and data science
• 

📚 Documentation

For comprehensive guides, API references, and tutorials, visit our official documentation at docs.plugged.in.

🤝 Contributing

We welcome contributions to all our projects! Whether you're interested in:

• Adding new features
• Fixing bugs
• Improving documentation
• Translating content
• Testing and reporting issues

Please check out our individual project repositories for specific contribution guidelines.

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Building the future of AI data exchanges, one protocol at a time.