How do I use S2 StreamStore MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@S2 StreamStore MCP Server list my basins and show me the streams in the 'production' one" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

S2 StreamStore MCP Server

An MCP server for S2 StreamStore built with Concierge progressive tool disclosure.

Instead of exposing all S2 API tools at once, the server guides AI agents through a natural workflow:

account → basin → stream

At each stage, only the relevant tools are visible.

Stages

Stage	Tools	Description
account	`list_basins`, `create_basin`, `select_basin`, `list_access_tokens`, `issue_access_token`, `revoke_access_token`, `account_metrics`	Manage basins and access tokens
basin	`get_basin_config`, `reconfigure_basin`, `delete_basin`, `list_streams`, `create_stream`, `select_stream`, `basin_metrics`, `go_back_to_account`	Manage streams within a basin
stream	`get_stream_config`, `reconfigure_stream`, `delete_stream`, `append_records`, `read_records`, `check_tail`, `stream_metrics`, `go_back_to_basin`	Read/write records and manage stream config

Setup

pip install -e .

Configuration

Set your S2 access token as an environment variable:

export S2_ACCESS_TOKEN="your-token-here"

Run

stdio (for Cursor, Claude Desktop, etc.):

python main.py

MCP Client Configuration

Add to your MCP client config (e.g. ~/.cursor/mcp.json):

{
  "mcpServers": {
    "s2": {
      "command": "python",
      "args": ["/path/to/mcp/main.py"],
      "env": {
        "S2_ACCESS_TOKEN": "your-token-here"
      }
    }
  }
}