Timeplus MCP Server

The Timeplus MCP Server bridges Claude (and other MCP‑compatible assistants) with the Timeplus data platform, enabling developers to query time‑series data and manage Kafka streams directly from natural language interactions. By exposing a set of SQL execution tools, database introspection helpers, and Kafka‑centric operations, the server turns a conversational AI into a powerful data analyst that can retrieve insights from real‑time streams without writing boilerplate code.

At its core, the server solves the friction of connecting an LLM to a time‑series database. Developers can ask questions like “Show me the last 24 hours of click traffic” or “Create a stream that ingests Kafka topic into Timeplus.” The server translates these prompts into SQL or administrative commands, runs them safely (defaulting to read‑only mode), and returns the results in a format that Claude can embed back into the conversation. This eliminates the need to manually craft SQL, manage credentials, or handle Kafka configurations in the client code.

Key capabilities include:

• Prompt augmentation: supplies the LLM with guidelines on how to write Timeplus‑specific SQL, improving query accuracy.
• SQL execution: runs arbitrary queries with optional read‑write control via an environment flag.
• Metadata discovery: , , and provide catalog information, enabling dynamic exploration.
• Kafka integration: shows sample messages, while automates the creation of a Timeplus stream that consumes Kafka data.
• Iceberg connectivity: allows the server to connect to Iceberg tables stored in S3, expanding analytical options.

Real‑world scenarios abound: a data engineer can prototype a new dashboard by asking the assistant to pull the latest metrics; a product analyst can generate ad‑hoc reports on streaming events without writing code; or an operations team can monitor Kafka health and automatically spin up streams when new topics appear. Because the server runs inside a secure, read‑only environment by default, it mitigates accidental data modification while still offering full read/write control when explicitly enabled.

Integrating the Timeplus MCP Server into an AI workflow is straightforward: once configured, any MCP‑compatible client (Claude Desktop, 5ire, etc.) will list the server as a tool provider. The assistant can then invoke these tools inline, receive immediate results, and continue the conversation—effectively turning a chat interface into a live data exploration platform. This tight coupling between natural language and database operations streamlines data access, reduces cognitive load for developers, and accelerates the time from insight to action.