simba-mcp 0.1.0

MCP server for Simba Marketing Mix Modeling — connect AI assistants to your MMM models

Simba MCP Server

Simba is a Bayesian Marketing Mix Modeling (MMM) platform. This MCP server lets AI assistants interact with your Marketing Mix Models directly — upload data, build models, check results, and run budget optimizations through natural language in Claude, Cursor, or Claude Code.

See Also

• getsimba.ai — the main Simba website (features, pricing, demos)
• getsimba-ai/simba-mmm — platform repo with full documentation on MMM concepts, data requirements, model configuration, optimization, and scenario planning

Installation

pip install simba-mcp

Or run directly without installing:

uvx simba-mcp

Quick Start

Cursor IDE

Add to your Cursor MCP settings (.cursor/mcp.json in the workspace or global settings):

{
  "mcpServers": {
    "simba": {
      "command": "uvx",
      "args": ["simba-mcp"],
      "env": {
        "SIMBA_API_URL": "https://app.getsimba.ai",
        "SIMBA_API_KEY": "simba_sk_..."
      }
    }
  }
}

Claude Code

Add to your Claude Code MCP config:

{
  "mcpServers": {
    "simba": {
      "command": "uvx",
      "args": ["simba-mcp"],
      "env": {
        "SIMBA_API_URL": "https://app.getsimba.ai",
        "SIMBA_API_KEY": "simba_sk_..."
      }
    }
  }
}

Claude API (MCP Connector)

Use the remote Streamable HTTP transport with the Anthropic MCP connector:

import anthropic

client = anthropic.Anthropic()

response = client.beta.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=4096,
    messages=[{"role": "user", "content": "List my Simba models"}],
    mcp_servers=[
        {
            "type": "url",
            "url": "https://app.getsimba.ai/mcp",
            "name": "simba",
            "authorization_token": "simba_sk_...",
        }
    ],
    tools=[{"type": "mcp_toolset", "mcp_server_name": "simba"}],
    betas=["mcp-client-2025-11-20"],
)

Available Tools

Tool	Description
get_data_schema	Get the canonical CSV schema for MMM input files
upload_data	Upload a CSV dataset to Simba
list_models	List all models with their status
create_model	Configure and start fitting a new MMM model
get_model_status	Poll fitting progress for a model
get_model_results	Get results (ROI, contributions, response curves, diagnostics, and more)
run_optimizer	Run budget optimization on a completed model
get_optimizer_results	Get optimizer status and results
get_scenario_template	Generate a forward-period template for scenario planning
run_scenario	Run a "what-if" scenario prediction
get_scenario_results	Get scenario prediction results

Example Prompts

Try these with any connected AI assistant:

Explore your models:

"List my Simba models and show me the channel ROI summary for the most recent complete model."

Build a model:

"Upload this CSV data to Simba and create a new MMM model with TV, Search, and Social as media channels. Use 'revenue' as the KPI and 'date' as the date column."

Check progress:

"What's the fitting status of model a1b2c3d4?"

Get results:

"Show me the model diagnostics and channel contributions for model a1b2c3d4."

Optimize budget:

"Run a budget optimization on model a1b2c3d4 with $1M total budget over 12 months. Set TV bounds to 5-40% and Search to 10-50%. Use uniform laydown weights."

Response curves:

"Show me the response curves for model a1b2c3d4. At what spend level does TV hit diminishing returns?"

Scenario planning:

"Get a scenario template for model a1b2c3d4 for the next 12 weeks. Then run a scenario where I increase TV by 20% and cut Search by 10%. What happens to revenue?"

Full workflow:

"I have marketing data I want to analyze. First get the schema so I know what format is needed, then upload my data, create a model, and once it's done show me the ROI by channel."

API Key Setup

The MCP server authenticates with the same API keys used by the Simba REST API. Create a key with the required scopes:

1. Go to Profile > API Keys in the Simba UI
2. Click Create Key
3. Set scopes: ingest, read:models, read:results, create:models, optimize, scenario
4. Copy the key (shown only once)

Set the key as the SIMBA_API_KEY environment variable in your MCP config.

Configuration

Environment Variable	Description	Default
SIMBA_API_URL	Simba API base URL	http://localhost:5005
SIMBA_API_KEY	Your Simba API key	(required)

Transport Modes

The server supports all MCP transport modes:

# stdio (default) — for Cursor, Claude Code
simba-mcp

# Streamable HTTP — for remote deployment
simba-mcp --transport streamable-http --port 8100

# SSE — legacy transport
simba-mcp --transport sse --port 8100

# Or via uvicorn directly
uvicorn "simba_mcp.server:create_app()" --host 0.0.0.0 --port 8100

License

MIT