MCP Servers

S2 StreamStore MCP Server

Enables interaction with S2 StreamStore to manage basins, access tokens, and data streams through a progressive tool disclosure workflow. It allows AI agents to efficiently navigate between account management, basin configuration, and stream-level operations like reading or writing records.

README

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"
      }
    }
  }
}

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