Data connectors

(MCP servers)

Give AI secure access to your databases, APIs, and tools. Model Context Protocol servers that provide clean, organized access to your information.

How it works

The bridge between your data & AI

MCP Servers act as a universal translator, giving AI structured access to all your systems.

Databases

APIs

Files

Streams

MCP

GPT-4

Claude

Gemini

Mistral

Your data sources AI Models

What MCP servers provide

Universal connectivity

Connect any data source or service to AI systems with standardized protocols.

Secure access

Enterprise-grade security with proper authentication and authorization layers.

High performance

Optimized data delivery with caching and intelligent routing for speed.

The process

How it works

Audit your data

We identify what data sources you have and how AI should access them.

Build the Bridge

We create MCP servers that expose your data in a clean, AI-friendly format.

Connect & Scale

Your AI systems get secure, structured access to all your data sources.

What we connect

Technical capabilities

Data sources we connect

Databases (SQL, NoSQL, Graph)
APIs (REST, GraphQL, gRPC)
File systems and cloud storage
Real-time streams and events
Legacy systems and mainframes

AI Integrations

OpenAI GPT models
Claude and other LLMs
Mistral, Llama, Qwen, DeepSeek
European-hosted private AI (via Scaleway)
Custom and self-hosted models
Multi-modal AI systems

FAQ

Common questions

What is MCP / Model Context Protocol?

MCP is a standard way for AI models to access external data and tools securely. Think of it as a universal adapter that lets AI 'plug into' your databases, APIs, and files.

Why do I need this instead of just giving AI my data?

Raw data access is messy and insecure. MCP provides structured, permission-controlled access, AI only sees what it needs, in a format it understands, with full audit trails.

Is my data safe?

Absolutely. MCP servers include encryption, access controls, and audit logging. Data can stay in your infrastructure or EU-hosted servers. Nothing is shared with third parties.

Do I need one if I already have APIs?

APIs are for apps. MCP is for AI. It adds context, caching, and AI-friendly formatting that makes your existing data sources much more useful for AI agents.

Ready to structure your data for AI?

Let's build MCP servers that make your data work for AI.

Discuss your needs