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GuideServerConfigure and deploy Tabsdata servers on your machine.TutorialsConfigure data integration workflows within a running Tabsdata server.Advanced TutorialsBuild end-to-end workflows between two specific systems.API ReferenceCLI ReferenceRelease Notes
Version: 2.0.2

Server

A Tabsdata Server is the top-level Tabsdata process deployed on a machine. It stores and manages Tabsdata resources, executes workflows, stores tabular data, and isolates Tabsdata processes from other processes running on the machine.

You can interact with a Server through the Tabsdata UI, CLI, Python API, or MCP integration.

Resources in a Server​

The main units of work within Tabsdata are Functions, which perform work on data, and Tables, which store data produced by Functions.

As the the top-level process Tabsdata, Servers store Functions and Tables as well as several organizational layers that nest functions and tables:

  1. Projects are the top-level workspaces within a Server. Projects isolate their resources and workflows from those in other Projects, allowing multiple teams or workflows to share a single Server without interfering with one another.
  2. Groups organize resources according to their role in a workflow. For example, a Project might have separate Groups for ingesting source data, cleaning data, and loading processed data.
  3. Collections define transaction boundaries for their Tables, determining how data is committed or rolled back during an execution. Collections are also credential stores that can provide Functions inside them with the credentials needed to connect to external systems.
Server
Projects
Groups
Collections
FunctionsConnectionsTables

Connecting to a Server​

A Server uses three dedicated endpoints by default: A server requires a dedicated public and private port and an ai agent port if integrating the Tabby conversational agent. By default, a server runs on the 2457 port making the server URI http://localhost:2457. 2458 private and 2459 for AI but this can be configured to allow multiple servers to run on a single machine.

  • A public endpoint runs on port 2457. The Tabsdata UI, tdk CLI, and Python API use this endpoint to communicate with the Server.
  • A private endpoint runs on port 2458. Tabsdata services use this endpoint for internal communication.
  • An AI agent endpoint runs on port 2459. The Tabsdata Conversational agent, Tabby, uses this endpoint.

The default local URI for the public endpoint is:

http://localhost:2457

You can connect to a Server using several interfaces:

  • The Tabsdata UI provides a browser-based interface for managing resources, running workflows, and inspecting results.
  • The tdk CLI provides command-line access to the Server.
  • The Python API provides programmatic access from Python applications.
  • The Tabsdata MCP integration allows AI agents to interact with the Server through tools.

Managing a Server​

The tdkserver CLI manages the Server lifecycle, including initializing, creating, starting, and stopping a Server.

See Initialize a Server, Create a Server, and Start a Server for setup instructions.

To connect an AI agent, see Connect an AI Agent.