MCP Server Demo

Name: MCP Server Demo
Author: never2average

@never2average

代码仓库

关于 MCP Server Demo

暂无概览

#mcp #task-management #kafka

基本信息

分类

其他

运行时

python

传输方式

stdio

发布者

never2average

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"
      ]
    }
  }
}

工具

未检测到工具

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.

FAQ from MCP Server Demo

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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