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:
- 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.
- 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.
- 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.
Connecting to a Server
A Tabsdata server uses three dedicated endpoints when running:
- A public endpoint runs on port
2457by default. The Tabsdata UI,tdkCLI, and Python API use this endpoint to communicate with the Server. - A private endpoint runs on port
2458by default. Tabsdata services use this endpoint for internal communication. - An AI agent endpoint runs on port
2459by default. The Tabsdata Conversational agent, Tabby, uses this endpoint.
Using default port configuration, 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
tdkCLI 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.