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MCP Server Demo

@never2average

リポジトリ

MCP Server Demo について

概要はまだありません

#mcp#task-management#kafka

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

never2average

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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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