
Mailgun MCP Server
OfficialConnects AI assistants to Mailgun email services for sending emails and analyzing delivery statistics through natural language commands.
A Model Context Protocol server implementation that enables AI assistants like Claude Desktop to interact with Mailgun email services, allowing users to send emails and visualize email delivery statistics through natural language.
What it does
- Send emails through Mailgun
- Retrieve and resend stored messages
- Query email delivery analytics and metrics
- Manage domains and DNS verification
- Create and update email webhooks
- Manage mailing lists and templates
Best for
About Mailgun MCP Server
Mailgun MCP Server is an official MCP server published by mailgun that provides AI assistants with tools and capabilities via the Model Context Protocol. Mailgun MCP Server lets AI assistants send emails via the Mailgun API and view email delivery analytics for seamless AI It is categorized under communication, analytics data.
How to install
You can install Mailgun MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
Mailgun MCP Server is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Mailgun MCP Server
Overview
A Model Context Protocol (MCP) server for Mailgun, enabling MCP-compatible AI clients to interact with the Mailgun email service.
Note: This MCP server runs locally on your machine. Mailgun does not currently offer a hosted version of this server.
Capabilities
- Messaging — Send emails, retrieve stored messages, resend messages
- Domains — View domain details, verify DNS configuration, manage tracking settings (click, open, unsubscribe)
- Webhooks — List, create, update, and delete event webhooks
- Routes — View and update inbound email routing rules
- Mailing Lists — Create and manage mailing lists and their members
- Templates — Create and manage email templates with versioning
- Analytics — Query sending metrics, usage metrics, and logs
- Stats — View aggregate statistics by domain, tag, provider, device, and country
- Suppressions — View bounces, unsubscribes, complaints, and allowlist entries
- IPs & IP Pools — View IP assignments and dedicated IP pool configuration
- Bounce Classification — Analyze bounce types and delivery issues
Prerequisites
- Node.js (v18 or higher)
- Mailgun account and API key
Quick Start
Configuration
Add the following to your MCP client configuration:
{
"mcpServers": {
"mailgun": {
"command": "npx",
"args": ["-y", "@mailgun/mcp-server"],
"env": {
"MAILGUN_API_KEY": "YOUR-mailgun-api-key",
"MAILGUN_API_REGION": "us"
}
}
}
}
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
MAILGUN_API_KEY | Yes | — | Your Mailgun API key |
MAILGUN_API_REGION | No | us | API region: us or eu |
Client-Specific Config Paths
- Claude Desktop (macOS):
~/Library/Application Support/Claude/claude_desktop_config.json - Claude Desktop (Windows):
%APPDATA%/Claude/claude_desktop_config.json - Claude Code: Run
claude mcp addor edit~/.claude.json
Sample Prompts
Send an Email
Can you send an email to EMAIL_HERE with a funny email body that makes it sound
like it's from the IT Desk from Office Space? Please use the sending domain
DOMAIN_HERE, and make the email from "postmaster@DOMAIN_HERE"!
Note: some MCP clients require a paid plan to invoke tools that send data. If sending fails silently, check your client's plan.
Fetch and Visualize Sending Statistics
Would you be able to make a chart with email delivery statistics for the past week?
Manage Templates
Create a welcome email template for new signups on my domain DOMAIN_HERE.
Include a personalized greeting and a call-to-action button.
Investigate Deliverability
Can you check the bounce classification stats for my account and tell me
what the most common bounce reasons are?
Troubleshoot DNS
Check the DNS verification status for my domain DOMAIN_HERE and tell me
if anything needs fixing.
Review Suppressions
Are there any unsubscribes or complaints for DOMAIN_HERE? Summarize the
top offenders.
Manage Routing Rules
List all my inbound routes and explain what each one does.
Create a Mailing List
Create a mailing list called announcements@DOMAIN_HERE and add these
members: [email protected], [email protected].
Compare Domains
Compare my sending volume and delivery rates across all my domains for
the past month.
Engagement by Region
Break down my email engagement by country and device for DOMAIN_HERE.
Review Tracking Settings
List all my domains and show which ones have tracking enabled for clicks
and opens.
Development
To run from source, clone the repository and use node directly:
git clone https://github.com/mailgun/mailgun-mcp-server.git
cd mailgun-mcp-server
npm install
npm test
In your MCP client config, replace the npx command with:
"command": "node",
"args": ["/path/to/mailgun-mcp-server/src/mailgun-mcp.js"]
Security Considerations
API key isolation
Your Mailgun API key is passed as an environment variable and is never exposed to the AI model itself — it is only used by the MCP server process to authenticate requests. The server does not log API keys, request parameters, or response data.
Local execution
The server runs locally on your machine. All communication with the Mailgun API is over HTTPS with TLS certificate validation enforced. No data is sent to third-party services beyond the Mailgun API.
API key permissions
Use a dedicated Mailgun API key with permissions scoped to only the operations you need. The server exposes read and update operations but does not expose any delete operations, which limits the blast radius of unintended actions.
Rate limiting
The server does not implement client-side rate limiting. Each tool call from the AI translates directly into a Mailgun API request. The server relies on Mailgun's server-side rate limits to prevent abuse — requests that exceed those limits will return an error to the AI assistant.
Prompt injection
As with any MCP server, a crafted or adversarial prompt could trick the AI assistant into calling operations you did not intend — for example, modifying tracking settings or reading mailing list members. Review your AI assistant's tool-call confirmations before approving actions, especially in untrusted prompt contexts.
Webhook URLs
Webhook create and update operations accept arbitrary URLs provided through the AI assistant. The MCP server passes these URLs to the Mailgun API without additional validation. Mailgun is responsible for validating webhook destinations. Ensure your AI assistant does not set webhook URLs to unintended internal or sensitive addresses.
Input validation
All tool parameters are validated against the Mailgun OpenAPI specification using Zod schemas. However, validation depends on the accuracy of the OpenAPI spec, and some edge-case parameters may fall back to permissive validation. The Mailgun API performs its own server-side validation as an additional layer of protection.
Debugging
The MCP server communicates over stdio. Refer to the MCP Debugging Guide for troubleshooting.
License
Apache 2.0 — see LICENSE for details.
Contributing
We welcome contributions! Please feel free to submit a Pull Request or open an Issue.
Alternatives
Related Skills
Browse all skillsWorld-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
Advanced content and topic research skill that analyzes trends across Google Analytics, Google Trends, Substack, Medium, Reddit, LinkedIn, X, blogs, podcasts, and YouTube to generate data-driven article outlines based on user intent analysis
Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence. Use PROACTIVELY for data analysis tasks, ML modeling, statistical analysis, and data-driven insights.
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
Comprehensive backend development guide for Langfuse's Next.js 14/tRPC/Express/TypeScript monorepo. Use when creating tRPC routers, public API endpoints, BullMQ queue processors, services, or working with tRPC procedures, Next.js API routes, Prisma database access, ClickHouse analytics queries, Redis queues, OpenTelemetry instrumentation, Zod v4 validation, env.mjs configuration, tenant isolation patterns, or async patterns. Covers layered architecture (tRPC procedures → services, queue processors → services), dual database system (PostgreSQL + ClickHouse), projectId filtering for multi-tenant isolation, traceException error handling, observability patterns, and testing strategies (Jest for web, vitest for worker).