---
title: "Integration Landscape"
description: "End-to-end view of the integration architecture in meinGPT"
canonical_url: "https://meingpt.com/en/docs/integrations/integration-landscape"
language: en
---

# Integration Landscape

> This page explains the architecture model.
> If you simply want to connect a service, start here: [Integrations Home](/en/docs/integrations).

## The Full Picture

In meinGPT, every integration type is reduced to one shared runtime model:

**LLM + tool calls as the central integration fabric.**

This allows very different systems to be operated, secured, and scaled in a consistent way.

## In 30 Seconds: What This Means for You

1. You connect systems through one integration model, not separately per assistant.
2. Your assistant selects the right tool or data source per task.
3. Security, permissions, and network access apply consistently across all integration types.

## Security and Access Model (Cross-cutting)

These layers apply across all integration types:

- Permissions and assistant sharing (users, teams, groups)
- Identity forwarding (JWT) for secure context propagation
- Cloud/on-prem connections (IP allowlisting, Enterprise Connection Network, VPN)

## Typical User Paths

| I want to... | Start here |
|--------------|------------|
| Connect Microsoft 365, Google, Jira, or Confluence | [Connectors Overview](/en/docs/integrations/connectors) |
| Make documents/files searchable as knowledge | [Data Pools (RAG)](/en/docs/integrations/data-pools-rag) |
| Query databases | [Databases Overview](/en/docs/integrations/databases-overview) |
| Connect internal APIs/services | [Custom MCP](/en/docs/integrations/custom-mcp-server) |
| Reach private systems in company networks | [Connections (Cloud/On-Prem)](/en/docs/integrations/connections-cloud-on-prem) |

## When to Use Which Building Block

| Building Block | Use Case |
|----------------|----------|
| **Connectors** | Execute actions in external tools (Slack, Jira, etc.) |
| **Databases** | Query structured data precisely (SQL, NoSQL) |
| **Data Pools (RAG)** | Retrieve and ground on document knowledge |
| **No-Code** | Integrate existing process automations (Make, Zapier) |
| **Custom MCP** | Connect customer-specific protocols/backends |
| **Custom AI Apps** | Provide guided custom UIs for specific workflows |

## Cloud Default vs. On-Prem Advanced

- Default: For most teams, setup in the meinGPT UI is sufficient.
- Advanced: On-prem/Outpost is for teams needing own runtime and network control.

## Related

- [Core Concepts](/en/docs/integrations/integration-core-concept)
- [Permissions](/en/docs/integrations/integration-permissions)
- [Connections (Cloud/On-Prem)](/en/docs/integrations/connections-cloud-on-prem)
- [Data Integration Guide](/en/docs/integrations/data-integration-guide)