Analitiq is a set of open-source tools for connecting APIs, databases, and storage systems — no coding required.
| Repository | What it does |
|---|---|
| AI Plugins | Claude Code plugins that build connectors and pipelines through conversation. |
| DIP Registry (this repo) | Open catalog of ready-made connector definitions for common systems. |
| Core Engine | Runs the pipelines — reads from sources, transforms data, writes to destinations. |
Use the plugins to create connectors and assemble pipelines. Connectors live in the registry. The engine executes the pipelines. Or skip the setup and use Analitiq Cloud for a fully managed experience.
Learn more at analitiq.ai.
If APIs and databases have standard interfaces, why can't we use AI to standardise how they talk to each other?
That's the question behind this project. Every API publishes documentation. Every database speaks SQL. The patterns are consistent -- authentication, pagination, filtering, schema discovery. Yet connecting systems still requires custom code, brittle scripts, and deep technical knowledge.
We're building an open registry of Data Integration Protocols (DIPs) -- machine-readable connector definitions that describe how to authenticate with a system, what data is available, and how to move it. These protocols are created and maintained using Claude, and validated by human contributors to research APIs, map data schemas, and produce standardised definitions that a data integration platform can consume.
We want to make it easier for anyone to connect their systems, to create a connection to any API or database within minutes using Claude code.
Claude plugin reads API documentation, database specs, and system references, then generates structured connector definitions following a strict protocol format. The result is a universal language for data movement -- no custom code, no vendor lock-in, no technical expertise required.
Each connector in this registry is a complete protocol definition:
- Authentication -- how to connect (OAuth2, API keys, database credentials, SSH tunnels)
- Endpoints -- what data is available and how to query it (API connectors)
- Schema discovery -- runtime detection of tables and fields (database connectors)
- Filters, pagination, rate limits -- the operational details that make integrations reliable
All connectors are listed as repositories in this organisation. The full registry is also available as machine-readable JSON:
https://raw.githubusercontent.com/analitiq-dip-registry/.github/main/registry.json
Connector categories are also available as machine-readable JSON:
https://raw.githubusercontent.com/analitiq-dip-registry/.github/main/categories.json
A cloud version with all the enterprise bells and whistles is on analitiq-app.com. Select a source and destination, and the platform handles the rest.
- Clone the analitiq-core repository
- Install the Claude plugin
analitiq-plugin-dataflow - Launch Claude and say: "I need to move data from X to Y"
The plugin fetches the required connectors from this registry and sets up the pipeline automatically.
Anyone can create a connector -- no programming required. Claude does the research, generates the protocol definition, and validates the result.
claude plugin add analitiq-ai/ai-plugins-official
Then say: "I want to create a connector for [system name]"
Claude will research the system's documentation, determine authentication methods, map available endpoints, and produce a complete, standardised connector definition.
This registry is community-maintained. See CONTRIBUTING.md for guidelines.
- Analitiq Cloud -- managed platform for running data integrations in the cloud
- AI Plugins -- open-source Claude Code plugins for building connectors and data pipelines
- Connector Template -- starting point for new connector definitions