MCP Server Demo

@never2average

代码仓库

基本信息

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其他

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stdio

作者

never2average

关于 MCP Server Demo

暂无概览

#mcp #task-management #kafka

MCP Server Demo 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "a2a-mcp-server": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

MCP Server Demo 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Server Demo?

MCP Server Demo is a production-ready task management system built with MCP (Model Control Protocol) and Kafka. It enables AI agents to interact with a Kafka-based task queue for task creation, updates, completion, and real-time notification handling.

How to use MCP Server Demo?

Install dependencies with pip install -e ., configure Kafka cluster details in kafka_config.py, and start the server with python main.py. Optionally load test data using python kafka_test_data.py. AI agents interact via exposed MCP tools for tasks and notifications.

Key features of MCP Server Demo

Task management: create, update, prioritize, complete tasks.
Real-time notification system with priority levels.
Kafka integration for reliable message queuing and event streaming.
AI-friendly MCP tools for task and notification operations.
Background consumer services for processing Kafka messages.

Use cases of MCP Server Demo

AI agents manage production tasks via MCP tools.
Real-time notification processing for task updates.
Background task queue processing with Kafka consumers.
Automated task prioritization and completion workflows.

常见问题

What are the runtime dependencies?

Python 3.13 or later, a Kafka cluster (local or AWS MSK), and the Confluent Kafka Python client.

How do I configure the Kafka connection?

Update the `KAFKA_CONFIG` dictionary in `kafka_config.py` with your bootstrap servers, security protocol (e.g., SASL_SSL), SASL mechanism (e.g., SCRAM-SHA-512), username, and password.

What MCP tools are exposed?

Task management tools: `fetch_queue`, `change_task_priority`, `pickup_task`, `complete_task`, `get_task_details`, `check_task_status`. Notification tools: `check_notification_count`, `get_notification_list`, `mark_notification_as_read`.

How can I populate test data?

Run `python kafka_test_data.py` to generate sample tasks and notifications for demonstration.

What license is used?

The project is distributed under the MIT License.

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