Jampp

Provides access to Jampp Reporting API via MCP, enabling retrieval of campaign spend, performance metrics, and async report results.

python

0

GitHub Stars

python

Language

7 months ago

First Indexed

3 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "springwq-jampp_mcp_server": {
      "command": "python",
      "args": [
        "jampp_mcp_server.py"
      ],
      "env": {
        "JAMPP_CLIENT_ID": "YOUR_CLIENT_ID",
        "JAMPP_CLIENT_SECRET": "YOUR_CLIENT_SECRET"
      }
    }
  }
}

Jampp MCP Server enables access to the Jampp Reporting API through the Model Context Protocol, letting you query campaign performance data with ease. It supports OAuth 2.0 authentication, GraphQL integration, and asynchronous report retrieval to empower LLM-driven reporting workflows.

How to use

You interact with the Jampp MCP Server through an MCP client. Start the server locally and connect your MCP client to the running process to fetch campaign spend, daily spend, and performance metrics. You can also create and monitor asynchronous reports for large data sets and then retrieve the results when they are ready.

To run, start the server from your terminal and point your MCP client at the local process. For development and testing, you can use a local inspector or an integration layer such as Claude Desktop to query the server and retrieve results for your campaigns.

How to install

Prerequisites you need before installing:

Python 3.10 or higher
Jampp API credentials (Client ID and Client Secret) to authorize access to the reporting data.

Step 1: Clone the project and navigate into the folder.

git clone https://github.com/yourusername/mcp-jampp.git
cd mcp-jampp

Step 2: Install dependencies. You can use the uvx/uvm tooling or plain pip to install the MCP CLI and required libraries.

uv add "mcp[cli]" httpx python-dotenv

Or with pip:

pip install "mcp[cli]" httpx python-dotenv

Step 3: Create an environment file with your Jampp credentials in the project root so the server can authenticate with the Jampp API.

JAMPP_CLIENT_ID=your_client_id
JAMPP_CLIENT_SECRET=your_client_secret

Additional sections

Server configuration and usage commonly involve running a local server process and optionally configuring an external client (for example, Claude Desktop) to issue queries against the MCP server.

Environment variables required for the server are JAMPP_CLIENT_ID and JAMPP_CLIENT_SECRET. Ensure these values are kept secure and not committed to version control.

Available tools

get_campaign_spend

Fetches campaign spend data for a specified date range and optional campaign ID.

get_campaign_daily_spend

Retrieves daily spend figures for a given campaign over a date range, with optional timezone support.

get_campaign_performance

Returns comprehensive performance metrics for campaigns within a date range, with optional campaign filtering.

create_async_report

Creates an asynchronous report for large datasets with specified dimensions and metrics.

get_async_report_status

Checks the status of an asynchronous report by its report_id.

get_async_report_results

Retrieves the results of a completed asynchronous report.

get_available_metrics_and_dimensions

Provides a list of all metrics and dimensions available for reporting.