AutotaskMCP

AutotaskMCP

Enables interaction with Autotask REST API for ticket management and querying through natural language.

Category
访问服务器

README

AutotaskMCP Server

MCP Server built with the MCP Builder [https://mcpbuilder.leniolabs.com] using the Streamable HTTP transport over ExpressJS.

Description

This MCP (Model Context Protocol) server provides tools for interacting with Autotask REST API services. It uses Express.js with Streamable HTTP transport to handle MCP requests.

Features

  • Streamable HTTP transport for MCP protocol
  • Express.js server for handling HTTP requests
  • Multiple Autotask API tools for ticket management and querying
  • Session management with proper cleanup

Prerequisites

  • Node.js 20 or higher
  • npm or yarn

Installation

npm install

Development

npm run dev

This will start the server in watch mode using tsx.

Building

npm run build

This compiles TypeScript to JavaScript in the dist/ directory.

Running

npm start

The server will start on port 3000 by default.

Docker

Build the Docker image

docker build -t autotaskmcp:latest .

Run the container

docker run -p 3000:3000 autotaskmcp:latest

Using Docker Compose

docker-compose up -d

Environment Variables

  • PORT - Port number for the server (default: 3000)
  • NODE_ENV - Node environment (default: production in Docker)

API Endpoints

  • POST /mcp - Handle MCP requests (initialization and subsequent requests)
  • GET /mcp - SSE stream for MCP responses
  • DELETE /mcp - Terminate MCP session

Configuration

Autotask API Credentials

The server requires Autotask API credentials to be configured. These can be set via environment variables:

  • AUTOTASK_API_INTEGRATION_CODE - Your Autotask API Integration Code
  • AUTOTASK_USER_NAME - Your Autotask API Username
  • AUTOTASK_SECRET - Your Autotask API Secret
  • AUTOTASK_IMPERSONATION_RESOURCE_ID - Your Autotask Impersonation Resource ID

These can be set:

  • As environment variables at runtime (recommended)
  • As build arguments during Docker build (baked into image)

Deployment

Deploying to Northflank

  1. Build Context: Set to . (the root directory where the Dockerfile is located)

  2. Port: Expose port 3000 to the internet

  3. Environment Variables: Set the following environment variables in Northflank:

    • AUTOTASK_API_INTEGRATION_CODE - Your Autotask API Integration Code
    • AUTOTASK_USER_NAME - Your Autotask API Username
    • AUTOTASK_SECRET - Your Autotask API Secret
    • AUTOTASK_IMPERSONATION_RESOURCE_ID - Your Autotask Impersonation Resource ID
    • PORT (optional) - Server port, defaults to 3000
    • NODE_ENV (optional) - Set to production
  4. Build Arguments (Optional - if you want to hardcode credentials into the image):

    • AUTOTASK_API_INTEGRATION_CODE
    • AUTOTASK_USER_NAME
    • AUTOTASK_SECRET
    • AUTOTASK_IMPERSONATION_RESOURCE_ID

    Note: If using build arguments, the credentials will be baked into the Docker image. If using environment variables, they can be changed without rebuilding.

Publishing

Publishing to GitHub

  1. Initialize Git repository (if not already done):

    git init
    git add .
    git commit -m "Initial commit"
    
  2. Create a GitHub repository and push:

    git remote add origin https://github.com/YOUR_USERNAME/autotaskmcp.git
    git branch -M main
    git push -u origin main
    

Publishing Docker Images (Optional)

Note: If you're deploying to Northflank or similar platforms that build from source, you don't need to publish images to a registry. The platform will build directly from your Dockerfile.

Option 1: GitHub Container Registry (Default - Automated)

The repository includes GitHub Actions workflows that automatically build and push to GitHub Container Registry (ghcr.io):

  1. Push to main/master branch:

    • The CI workflow automatically builds and pushes on every push
    • Images are published to: ghcr.io/YOUR_USERNAME/autotaskmcp:latest
    • No additional setup required (uses GitHub token automatically)
  2. Create a release:

    • Create a GitHub release to trigger versioned tags
    • The docker-publish.yml workflow handles release builds

Option 2: Manual Build and Push to GitHub Container Registry

  1. Build the Docker image:

    docker build -t ghcr.io/YOUR_USERNAME/autotaskmcp:latest .
    
  2. Login to GitHub Container Registry:

    echo $GITHUB_TOKEN | docker login ghcr.io -u YOUR_USERNAME --password-stdin
    
  3. Push the image:

    docker push ghcr.io/YOUR_USERNAME/autotaskmcp:latest
    

Option 3: Docker Hub (Optional - Manual Setup Required)

If you prefer Docker Hub, you can manually build and push:

  1. Build the Docker image:

    docker build -t YOUR_DOCKERHUB_USERNAME/autotaskmcp:latest .
    
  2. Login to Docker Hub:

    docker login
    
  3. Push the image:

    docker push YOUR_DOCKERHUB_USERNAME/autotaskmcp:latest
    

Note: The GitHub Actions workflows use GitHub Container Registry by default. To use Docker Hub with GitHub Actions, you would need to:

  • Add DOCKER_USERNAME and DOCKER_PASSWORD secrets to your repository
  • Modify the workflows to use Docker Hub instead of GHCR

License

MIT

Author

MCP Builder https://mcpbuilder.leniolabs.com

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选