mxmcp-py
mxHERO Mail2Cloud Advanced MCP
Documentation
MCP Server for mxHERO Multi-Account Email Search
Description
This MCP (model context protocol) server is a Python project that provides access to mxHERO's Mail2Cloud Advanced multi-account email search service.
The Model Context Protocol (MCP) is a framework designed to standardize the way models interact with various data sources and services. In this project, MCP is used to facilitate seamless integration to mxHERO Mail2Cloud Advanced. Mail2Cloud Advanced is a high performance data service for a company's email data. Mail2Cloud Advanced connects to company email services and optimizes the content for fast, scalable and secure access by AI solutions.
Architecture
Mail2Cloud is designed to selectively capture emails from one or more accounts. The selection of emails can be finely controlled by powerful filters examining any aspect of messages and their attachments. Captured emails are then optimized and stored into an isolated tenant in a vector database designed for email related searches. This MCP accesses the stored emails in the tenant through authenticated access credentials.
Advantages
Solutions built with Mail2Cloud Advanced MCP outperforms other AI solutions with regards to email data search & knowledge recovery (study)
- Provides secure links to original emails (safe from accidental user deletion, etc.)
- Allows LLMs to search massive email repositories, far beyond their context window restraints.
Demo Accounts
To facilitate exploration of this MCP, mxHERO provides demo accounts that are pre-loaded with thousands of emails. More about the demo emails can be found here.
> See 'Access Tokens' below to get a token.
For more information see: mxHERO Mail2Cloud Advanced multi-email account service, including architecture, and optimizations.
Alternate versions
A Go version (plus prebuilt binaries) can be found here.
Streamable HTTP
This MCP repo is the 'stdio' variant. HTTP options exist at the following addresses:
- https://lab4-api.mxhero.com/mcp/connect (streamable HTTP)
- https://lab4-api.mxhero.com/mcp/sse (Legacy SSE)
Tools implemented
`email_search`
Search stored emails
Parameters
- `query` (str): Email search query
Returns JSON of search results
Requirements
- Python 3.13 or higher
- mxHERO Vector Search token
Access Tokens
- A demo token can be obtained at https://lab4-api.mxhero.com/demo_signup
- For production tokens, uncheck "Demo" and Request an account (or contact mxHERO at contact@mxhero.com).
Installation
1. Clone the repository
git clone https://github.com/mxaiorg/mxmcp-py2. Install `uv` if not installed yet:
2.1 MacOS+Linux
curl -LsSf https://astral.sh/uv/install.sh | sh2.2 Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"3. Create and set up our project:
3.1 MacOS+Linux
# Create virtual environment and activate it
uv venv
source .venv/bin/activate
# Lock the dependencies
uv lock3.2 Windows
# Create virtual environment and activate it
uv venv
.venv\Scripts\activate
# Lock the dependencies
uv lockUsage
Running the MCP Server
To start the MCP server, run the following command:
uv --directory /fullpath/PycharmProjects/mxmcp-py run src/mxmcp.py --token "my_token"Typically you don't need to start the server, your client will do it, but it is useful to make sure things are working.
Using Claude as the client
1. Edit your `claude_desktop_config.json`:
code ~/Library/Application\ Support/Claude/claude_desktop_config.json...or use your favorite json editor.
2. Add the configuration:
- Replace the --directory argument value ('/Users/...') with the absolute (full) path to the python script.
{
"mcpServers": {
"mxhero-mcp-server": {
"command": "uv",
"args": [
"--directory",
"/Users/your_user/Desktop/mxmcp-py",
"run",
"src/mxmcp.py",
"--token",
""
]
}
}
}MCP library
https://gofastmcp.com/servers/tools
Notice
Using this client against the hosted service requires an account/API key and is governed by our ToS.
Frequently asked questions
What is mxmcp-py?
mxmcp-py is mxHERO Mail2Cloud Advanced MCP
How do I install mxmcp-py?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is mxmcp-py open source?
Yes — it is hosted on GitHub at https://github.com/mxaiorg/mxmcp-py.
Related MCP tools
🙌 OpenHands: Code Less, Make More for the Model Context Protocol. Enhance AI assistants with powerful integrations. Python-based implementation.
Universal memory layer for AI Agents; Announcing OpenMemory MCP - local and secure memory management. Python-based implementation.
基于大模型搭建的聊天机器人,同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入,可选择ChatGPT/Claude/DeepSeek/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Kimi/LinkAI,能处理文本、语音和图片,访问操作系统和互联网,支持基于自有知识库进行定制企业智能客服。
An LLM agent that conducts deep research (local and web) on any given topic and generates a long report with citations. Built for the Model Context Protocol to
🚀 The fast, Pythonic way to build MCP servers and clients Trusted by 19900+ developers. Trusted by 19900+ developers. Trusted by 19900+ developers.
🔥 MaxKB is an open-source platform for building enterprise-grade agents. MaxKB 是强大易用的开源企业级智能体平台。 for the Model Context Protocol. Enhance AI assistants with po
Run your own MCP server? See who uses it and what to fix.
Measure it with TrackMCP