custom-mcp-server
A Model Context Protocol server that provides calculator operations, n8n workflow automation, customer support resources, and content creation prompts.
README
Custom MCP Server: Calculator & Workflow Automation
This is a custom Model Context Protocol (MCP) server built with Python using the FastMCP framework. It provides a set of calculator tools, resources for customer support, and prompts for content creation, along with integration to external n8n workflows.
Features
🛠️ Tools
Tools allow the AI model to perform actions or computations.
add(a, b): Add two numbers.subtract(a, b): Subtract two numbers.multiply(a, b): Multiply two numbers.divide(a, b): Divide two numbers (handles division by zero).trigger_n8n_workflow(prompt): Triggers a remote n8n workflow via webhook, sending a prompt and returning the response.
📚 Resources
Resources provide context and data to the AI model.
calculator://support-playbook: Reads and returns the content of the "Customer Support Playbook" (resource_exampe.md).
📝 Prompts
Prompts provide structured templates for the AI model to generate content.
webinar_blog_post: A template to convert a webinar transcript into an engaging blog post. requires:webinar_title,webinar_date,speakers,transcript.
Prerequisites
- Python 3.10+ (Recommend managing with
uv) - uv: A fast Python package installer and resolver.
- npx: Required if you want to use the MCP Inspector for testing.
Installation & Setup
-
Clone or Navigate to the Project Directory
-
Install Dependencies Use
uvto sync the project dependencies:uv sync -
Configure Environment Variables This server requires environment variables for the n8n integration.
Create a
.envfile from the example:cp .env.example .envOpen
.envand configure your settings:N8N_WEBHOOK_URL=https://your-n8n-instance.com/webhook/... N8N_HEADER_NAME=Your-Header-Name N8N_HEADER_VALUE=Your-Header-ValueNote: If
N8N_HEADER_NAMEandN8N_HEADER_VALUEare set, they will be included in the webhook request headers.
Usage
🔍 Testing with MCP Inspector
The MCP Inspector is a developer tool to test your server's tools, resources, and prompts in a web interface.
Run the follow command:
npx @modelcontextprotocol/inspector uv run server.py
This will launch a local server (usually at http://localhost:5173) where you can interact with your MCP server.
🤖 Integration with Claude for Desktop
To use this server with the Claude desktop app:
-
Locate Configuration File:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
-
Update Configuration: Add the server configuration to the
mcpServersobject. You can copy the contents of theclaude_desktop_config.jsonfile provided in this repository.{ "mcpServers": { "calculator": { "command": "uv", "args": ["--directory", "/ABSOLUTE/PATH/TO/THIS/PROJECT", "run", "server.py"] } } }Important: Replace
/ABSOLUTE/PATH/TO/THIS/PROJECTwith the actual absolute path to this directory on your machine. -
Restart Claude: Restart the Claude application to load the new server.
Troubleshooting
- Timeout Errors: The n8n workflow trigger has a 30-second timeout. If your workflow takes longer, you may need to increase this in
server.py. - Missing Environment Variables: Ensure your
.envfile is properly set up and that you are running the server from the project root where the.envfile is located. - Claude Connection Issues: Check Claude's logs for connection details. Ensure the absolute path in the config file is correct.
Project Structure
server.py: Main MCP server implementation.resource_exampe.md: Source file for the support playbook resource.prompt.md: Template file for the blog post prompt..env: (Ignored by git) Local configuration for secrets.pyproject.toml: Python project and dependency definition.
推荐服务器
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。
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。
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。
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。
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。
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。
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。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
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。