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s2-streamstore

S2 StreamStore MCP Server

by s2-streamstore
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Python
Remote

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

Related MCP server: Databricks MCP Server

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"
      }
    }
  }
}

This server cannot be installed

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Maintenance

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