Northbeam MCP Server
# Northbeam MCP Server
This is a Model Context Protocol (MCP) server for accessing Northbeam marketing analytics data. It provides tools and resources for querying metrics, dimensions, channel performance, cohort analysis, and attribution data from Northbeam.
## Setup
1. Install dependencies:
```
npm install
```
2. Create a `.env` file with your Northbeam API key and brand name:
```
NORTHBEAM_API_KEY=your_api_key_here
NORTHBEAM_BRAND=your_brand_name_here
```
3. Run the server:
```
npm run dev
```
## Testing with MCP Inspector
You can test the server using the MCP Inspector:
```
npm run inspect
```
This will open a web interface where you can test all the available tools and resources.
## Available Tools
- `get_metric`: Get metric data from Northbeam
- `list_metrics`: List all available metrics in Northbeam
- `list_dimensions`: List all available dimensions in Northbeam
- `get_channel_performance`: Get channel performance data from Northbeam
- `get_cohort_analysis`: Get cohort analysis data from Northbeam
- `get_attribution`: Get attribution data from Northbeam
## Available Resources
- `northbeam://metrics/{metric_name}`: Get data for a specific metric
## Usage as a Package
You can also use this as an npm package:
```
npx northbeam-mcp
```
Or with the inspector:
```
npx @modelcontextprotocol/inspector npx northbeam-mcp
```
TDQS
Scored across 6 tools
Each tool targets a distinct action: listing vs getting metrics, listing dimensions, and three analysis types (channel performance, cohort, attribution). The purposes are clearly separated by resource type and analysis focus.
All tools follow a consistent verb_noun pattern: list_ for enumeration and get_ for single items or report-style analyses. The naming is predictable and easy to generalize.
Six tools is well-scoped for an analytics server, covering exploration (metrics, dimensions) and core analytical operations without being either sparse or overwhelming.
The set covers metric listing/retrieval, dimension listing, and key analytical views. A minor gap is the absence of a way to list specific channels or cohorts directly, but the existing tools likely cover these indirectly via parameters.