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LimeAI MCP Server (Python)

LimeAI MCP Server (Python)

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github.com/liuwenlonghubAI & Agents0Updated 68w ago

About LimeAI MCP Server (Python)

LimeAI MCP Server (Python) is a Python MCP server repository for connecting LimeAI with MCP-compatible clients. It requires Python 3.10 or later and a LimeAI access token.

Key features

  1. 01Python 3.10 or later
  2. 02LimeAI access token configuration
  3. 03Setup instructions for Cursor and similar clients

Use cases

  1. 01Connecting LimeAI to Cursor
  2. 02Configuring LimeAI in another MCP client

MCP support

It provides the LimeAI MCP server for use from Cursor and other MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

LimeAI MCP Server (Python)

环境要求
  • Python 3.10 或更高版本。

1. 设置环境

首先,我们来安装uv:

MacOS/Linux

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

2. 获取 LimeAI MCP Server

# LimeAI Mcp Server 官方开源仓库下载
[email protected]:liuwenlonghub/limeai-mcp-server.git
cd limeai-mcp-server

# 创建虚拟环境并激活
uv venv
source .venv/bin/activate

# 安装依赖
uv add "mcp[cli]" httpx

获取 LIMEAI_ACCESS_TOKEN

3. 在Cursor中使用

Cursor -> Preferences -> Cursor Settings -> MCP -> Add new global MCP

添加以下配置内容(其它MCP客户端类似):

{
  "mcpServers": {
      "limeai-mcp-server": {
        "command": "uv",
        "args": [
          "--directory",
          "{YOUR_PATH}/limeai-mcp-server/",
          "run",
          "main.py"
        ],
        "env": {
        "LIMEAI_ACCESS_TOKEN": "<USER_LIMEAI_ACCESS_TOKEN>"
        }
      }
    }
}

回到配置,此时 LimeAI MCP Server已经启用

Comments

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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.