Zammad客服助手MCP 是 AI Skill Hub 本期精选MCP工具之一。综合评分 7.8 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。
为Zammad客服系统的开源MCP服务器,通过Model Context Protocol标准接入Claude等AI助手,实现客户支持自动化和智能回复。适合需要强化客服效能的企业和开发者集成使用。
Zammad客服助手MCP 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
为Zammad客服系统的开源MCP服务器,通过Model Context Protocol标准接入Claude等AI助手,实现客户支持自动化和智能回复。适合需要强化客服效能的企业和开发者集成使用。
Zammad客服助手MCP 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/basher83/Zammad-MCP
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"zammad----mcp": {
"command": "npx",
"args": ["-y", "zammad-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 Zammad客服助手MCP 执行以下任务... Claude: [自动调用 Zammad客服助手MCP MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"zammad____mcp": {
"command": "npx",
"args": ["-y", "zammad-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
An MCP server that connects AI assistants to Zammad, providing tools for managing tickets, users, organizations, and attachments.
Disclaimer: This project is not affiliated with or endorsed by Zammad GmbH or the Zammad Foundation. This is an independent integration that uses the Zammad API.
See SECURITY.md for complete documentation.
uv pip install -e ".[dev]"
For production or containerized deployments:
```bash
docker run --rm -i \ -e ZAMMAD_URL=https://your-instance.zammad.com/api/v1 \ -e ZAMMAD_HTTP_TOKEN_FILE=/run/secrets/token \ -v ./secrets/zammad_http_token.txt:/run/secrets/token:ro \ ghcr.io/basher83/zammad-mcp:latest
The server supports Streamable HTTP transport for remote deployments.
Set these environment variables to enable HTTP transport:
export MCP_TRANSPORT=http # Enable HTTP transport
export MCP_HOST=127.0.0.1 # Host to bind (default: 127.0.0.1)
export MCP_PORT=8000 # Port to listen on
Direct Python:
MCP_TRANSPORT=http \
MCP_HOST=127.0.0.1 \
MCP_PORT=8000 \
ZAMMAD_URL=https://your-instance.zammad.com/api/v1 \
ZAMMAD_HTTP_TOKEN=your-api-token \
uvx --from git+https://github.com/basher83/zammad-mcp.git mcp-zammad
Docker:
docker run -d \
--name zammad-mcp-http \
-p 8000:8000 \
-e MCP_TRANSPORT=http \
-e MCP_HOST=0.0.0.0 \
-e MCP_PORT=8000 \
-e ZAMMAD_URL=https://your-instance.zammad.com/api/v1 \
-e ZAMMAD_HTTP_TOKEN=your-api-token \
ghcr.io/basher83/zammad-mcp:latest
Access the MCP endpoint at http://localhost:8000/mcp/.
⚠️ SECURITY WARNING: Bind to 0.0.0.0 only behind a reverse proxy with TLS.
Use a reverse proxy (nginx/Caddy) for HTTPS and security:
Example with Caddy:
```bash
```bash
uv pip install -e ".[dev]" ```
docker run --rm -i \ -e ZAMMAD_URL=https://your-instance.zammad.com/api/v1 \ -e ZAMMAD_HTTP_TOKEN=your-api-token \ ghcr.io/basher83/zammad-mcp:latest
```bash
Run without installation:
```bash
ZAMMAD_URL=https://your-instance.zammad.com/api/v1 \ ZAMMAD_HTTP_TOKEN=your-api-token \ uvx --from git+https://github.com/basher83/zammad-mcp.git mcp-zammad ```
docker run --rm -i \ --env-file .env \ ghcr.io/basher83/zammad-mcp:latest
#### Docker Image Versioning
The project publishes Docker images with semantic versioning:
- `latest` - Most recent stable release
- `1.2.3` - Specific version (recommended for production)
- `1.2` - Latest patch of 1.2 minor release
- `1` - Latest minor/patch of 1.x major release
- `main` - Latest main branch (may be unstable)
bash
To contribute or modify the code:
```bash
The server requires Zammad API credentials. Use a .env file:
cp .env.example .env
.env with your Zammad credentials: # Required: Zammad instance URL (include /api/v1)
ZAMMAD_URL=https://your-instance.zammad.com/api/v1
# Authentication (choose one method):
# Option 1: API Token (recommended)
ZAMMAD_HTTP_TOKEN=your-api-token
# Option 2: OAuth2 Token
# ZAMMAD_OAUTH2_TOKEN=your-oauth2-token
# Option 3: Username/Password
# ZAMMAD_USERNAME=your-username
# ZAMMAD_PASSWORD=your-password
# Optional: Disable TLS certificate verification (NOT recommended for production)
# Truthy values only: 1, true, yes, on. Unset (default) keeps TLS verification enabled.
# ZAMMAD_INSECURE=true
# Optional: Logging level (default: INFO)
# Valid values: DEBUG, INFO, WARNING, ERROR, CRITICAL
# LOG_LEVEL=INFO
# Optional: Transport Configuration
# MCP_TRANSPORT=stdio # Transport type: stdio (default) or http
# MCP_HOST=127.0.0.1 # Host address for HTTP transport
# MCP_PORT=8000 # Port number for HTTP transport
.env file on startup.| Variable | Default | Description |
|---|---|---|
MCP_TRANSPORT | stdio | Transport type: stdio or http |
MCP_HOST | 127.0.0.1 | Host address for HTTP transport |
MCP_PORT | - | Port number for HTTP transport (required if MCP_TRANSPORT=http) |
Important: Keep your .env file out of version control (already in .gitignore).
ZAMMAD_URL=https://instance.zammad.com/api/v1 ZAMMAD_HTTP_TOKEN=token python -m mcp_zammad ```
uv venv
MCP_TRANSPORT=http \ MCP_HOST=0.0.0.0 \ MCP_PORT=8000 \ ZAMMAD_URL=https://your-instance.zammad.com/api/v1 \ ZAMMAD_HTTP_TOKEN=your-api-token \ uvx --from git+https://github.com/basher83/zammad-mcp.git mcp-zammad
**Caddyfile configuration:**
caddy mcp.yourdomain.com { reverse_proxy localhost:8000 # Caddy automatically handles HTTPS/TLS }
**Production checklist:**
1. Use `MCP_HOST=0.0.0.0` only behind a reverse proxy
2. Enable HTTPS/TLS via reverse proxy
3. Implement authentication at the proxy or application layer
4. Restrict access with firewall rules
#### Client Configuration for HTTP
Configure your MCP client to use HTTP transport:
json { "mcpServers": { "zammad": { "url": "http://localhost:8000/mcp/" } } } ```
MCP_HOST=127.0.0.1 (localhost only)To generate an API token in Zammad:
创新的MCP集成方案,��Zammad与AI助手连接,降低客服成本。代码质量良好,但社区活跃度一般,商业化潜力较大。
该工具使用 AGPL-3.0 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
⚠️ AGPL 3.0 — 最严格的 Copyleft,网络服务端使用也需开源,SaaS 使用受限。
经综合评估,Zammad客服助手MCP 在MCP工具赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | Zammad-MCP |
| Topics | 客服系统MCP协议API集成自动化 |
| GitHub | https://github.com/basher83/Zammad-MCP |
| License | AGPL-3.0 |
| 语言 | Python |
收录时间:2026-05-23 · 更新时间:2026-05-23 · License:AGPL-3.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端