by universal-mcp
Braze is a Universal MCP (Model Context Protocol) server that provides a standardized interface for interacting with Braze's tools and services through a unified API. It is designed for managing customer engagement, user profiles, and messaging campaigns.
Braze is a Universal MCP (Model Context Protocol) server that provides a standardized interface for interacting with Braze's tools and services through a unified API. It is built using the Universal MCP framework and ensures compatibility with other MCP-compliant services and tools.
YouThe easiest way to start using Braze is directly from agentr.dev. Visit agentr.dev/apps and enable Braze. If you are new to Universal MCP, follow the setup instructions at agentr.dev/quickstart.
To set up Braze for local development, you will need Python 3.11+ and uv (install globally with pip install uv
).
uv sync
to install all dependencies from pyproject.toml
into a local virtual environment (.venv
).source .venv/bin/activate
.venv\Scripts\Activate
mcp dev src/universal_mcp_braze/server.py
and note the address and port.mcp install src/universal_mcp_braze/server.py
../src/universal_mcp_braze/README.md
.Braze is designed for managing customer engagement, user profiles, and messaging campaigns. Potential use cases include:
./src/universal_mcp_braze/README.md
within the project repository.uv
installed globally.This repository contains an implementation of an Braze Universal MCP (Model Context Protocol) server. It provides a standardized interface for interacting with Braze's tools and services through a unified API.
The server is built using the Universal MCP framework.
This implementation follows the MCP specification, ensuring compatibility with other MCP-compliant services and tools.
You can start using Braze directly from agentr.dev. Visit agentr.dev/apps and enable Braze.
If you have not used universal mcp before follow the setup instructions at agentr.dev/quickstart
The full list of available tools is at ./src/universal_mcp_braze/README.md
Ensure you have the following before you begin:
pip install uv
)Follow the steps below to set up your development environment:
Sync Project Dependencies
uv sync
This installs all dependencies from pyproject.toml
into a local virtual environment (.venv
).
Activate the Virtual Environment
For Linux/macOS:
source .venv/bin/activate
For Windows (PowerShell):
.venv\Scripts\Activate
Start the MCP Inspector
mcp dev src/universal_mcp_braze/server.py
This will start the MCP inspector. Make note of the address and port shown in the console output.
Install the Application
mcp install src/universal_mcp_braze/server.py
.
โโโ src/
โ โโโ universal_mcp_braze/
โ โโโ __init__.py # Package initializer
โ โโโ server.py # Server entry point
โ โโโ app.py # Application tools
โ โโโ README.md # List of application tools
โโโ tests/ # Test suite
โโโ .env # Environment variables for local development
โโโ pyproject.toml # Project configuration
โโโ README.md # This file
This project is licensed under the MIT License.
Generated with MCP CLI โ Happy coding! ๐
Please log in to share your review and rating for this MCP.
Discover more MCP servers with similar functionality and use cases
by open-strategy-partners
A Model Context Protocol (MCP) server that empowers LLMs to use some of Open Srategy Partners' core writing and product marketing techniques.
by trypeggy
facebook-ads-library-mcp is a Model Context Protocol (MCP) server that allows users to search Facebook's public ad library. It enables analysis of advertising strategies, ad content, and competitive landscapes for companies and brands.
by gomarble-ai
Facebook Ads MCP Server is an interface that provides programmatic access to Facebook Ads data and management features. It allows users to automate interaction with their Facebook advertising campaigns and integrate ad data into other systems.
by fetchSERP
Provides access to all FetchSERP API endpoints for SEO analysis, keyword research, SERP retrieval, and web scraping through an MCP server.
by AudienseCo
mcp-audiense-insights is a tool that connects AI agents to the Audiense Insights platform. It enables AI agents to access and analyze marketing insights and audience data for various use cases like market research and content strategy.
by data-skunks
Provides keyword research capabilitiesโincluding People Also Ask questions, Google autocomplete suggestions, Reddit and Quora queries, and semantic keyword extractionโthrough a Model Context Protocol (MCP) server that integrates with KeywordsPeopleUse.
by MarketplaceAdPros
amazon-ads-mcp-server is a server that facilitates interaction with Amazon Advertising data. It allows users to connect their Amazon Advertising accounts to access various advertising resources and reports, enabling automated ad management, custom reporting, and integration with AI/ML models.
by netdata
Real-time, perโsecond infrastructure monitoring platform that provides instant insights, autoโdiscovery, edgeโbased machineโlearning anomaly detection, and lightweight visualizations without requiring complex configuration.
by zed-industries
Provides real-time collaborative editing powered by Rust, enabling developers to edit code instantly across machines with a responsive, GPU-accelerated UI.