About Mailchimp
Mailchimp is an MCP server that integrates the email marketing and automation platform with GenAI applications. It provides broad API coverage, multiple authentication options, and mechanisms for handling requests and errors.
Key features
- 01Broad Mailchimp API coverage
- 02Multiple authentication methods
- 03Rate limiting
- 04Error handling and retries
- 05Asynchronous support
Use cases
- 01Connecting GenAI applications to Mailchimp
- 02Handling API requests with retry logic
MCP support
Exposes Mailchimp API integration through an MCP server for GenAI applications.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
uvx mailchimp-mcp-serverMAILCHIMP_API_KEYSecretAPI Key for MAILCHIMPMAILCHIMP_API_URLAPI URL for MAILCHIMPLocal servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMailchimp MCP Server
A Model Context Protocol (MCP) server for integrating Mailchimp with GenAI applications.
Overview
Email marketing and automation platform
Features
- Comprehensive Mailchimp API coverage
- Multiple authentication methods
- Enterprise-ready with rate limiting
- Full error handling and retry logic
- Async support for better performance
Installation
pip install mailchimp-mcp-server
Or install from source:
git clone https://github.com/asklokesh/mailchimp-mcp-server.git
cd mailchimp-mcp-server
pip install -e .
Configuration
Create a .env file or set environment variables according to Mailchimp API requirements.
Quick Start
from mailchimp_mcp import MailchimpMCPServer
# Initialize the server
server = MailchimpMCPServer()
# Start the server
server.start()
License
MIT License - see LICENSE file for details
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.