Ticket Tailor API Integration MCP Server

@shakermakerk

代码仓库

基本信息

分类

开发工具

许可证

MIT license

传输方式

stdio

作者

shakermakerk

关于 Ticket Tailor API Integration MCP Server

暂无概览

#ticket-tailor#api-integration#python-wrapper

Ticket Tailor API Integration MCP Server 配置

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代码仓库

Ticket Tailor API Integration MCP Server 工具

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概览

What is Ticket Tailor API Integration?

A Python MCP wrapper for the Ticket Tailor API that enables LLMs to interact with Ticket Tailor. It is aimed at developers building AI agents that need to retrieve events, orders, and perform actions on ticket data.

How to use Ticket Tailor API Integration?

Clone the repository, install dependencies, and create a .env file with your Ticket Tailor API key. Use the MCP server with Cursor by editing mcp.json or integrate it with your own agent frameworks (e.g., LangChain React agents). An example agent script is provided in example_langgraph_agent.py.

Key features of Ticket Tailor API Integration

Retrieve events with flexible filtering options
Fetch orders with comprehensive search parameters
Built on FastMCP for easy integration
Example agent included for LangChain React agents
Roadmap for implementing more API endpoints

Use cases of Ticket Tailor API Integration

Allow AI assistants to search and list events from Ticket Tailor
Enable chatbots to look up order information for customers
Build automated tools that manage ticket inventory and orders
Create AI-driven event management workflows

常见问题

What are the installation requirements?

Python 3 and dependencies from `requirements.txt`. You also need a Ticket Tailor API key.

How do I configure the server?

Create a `.env` file in the root directory and add your Ticket Tailor API key based on the `.env_example` file.

Can I use this server with any LLM framework?

Yes, the server follows the MCP protocol. The README provides an example for LangChain React agents in `example_langgraph_agent.py`.

Does the server cover all Ticket Tailor API endpoints?

Not yet. Only retrieving events and orders are implemented. The project roadmap lists prioritized endpoints for future implementation.

How do I integrate with Cursor?

Edit `mcp.json` to add a command entry: `"command": "mcp run /src/ticket_tailor/ticket_tailor_funcs.py"` (path may need adjustment).

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