Yokan Board MCP
Enables AI agents to interact with Yokan Kanban Board API to manage boards, columns, and tasks through a tool-based interface.
README
Yokan Board MCP
<p align="center"> <img src="./images/avatar.png" alt="Yokan Logo" width="150" style="border-radius: 50%;"> </p>
This project is a Model Context Protocol (MCP) server for the Yokan Kanban Board API. It provides a tool-based interface for AI agents to interact with and manage Kanban boards, columns, and tasks.

Features
- Board Management: Create, retrieve, update, and delete Kanban boards.
- Column Management: Create, retrieve, update, reorder, and delete columns within a board.
- Task Management: Create, retrieve, update, move, and delete tasks.
- Agent-Ready: Designed to be used by AI agents via the Master Control Protocol.
Tech Stack
Getting Started
Building and Running Docker Image
For new users or those who want to run the server without setting up a development environment, we recommend using Docker.
-
Build the Docker image:
docker build -t yokanboard/yokan-mcp . -
Run the Docker container:
docker run -p 8888:8888 --name yokan-mcp -e YOKAN_API_BASE_URL=http://your-yokan-api-host:port/api yokanboard/yokan-mcpMake sure to replace
http://your-yokan-api-host:port/apiwith the actual URL of your Yokan API instance.
MCP Clients Configuration
Gemini CLI with the Streamable Transport
Create .gemini/settings.json with the following content:
{
"mcpServers": {
"yokan-board": {
"httpUrl": "http://[your-yokan-mcp-host]:8888/mcp",
"headers": {
"Authorization": "Bearer [TOKEN]",
"accept": "application/json"
}
}
}
}
VS Code Copilot with the Stdio Transport
Create .vscode/mcp.json file with the following content:
{
"servers": {
"yokan-board": {
"type": "stdio",
"command": "uv",
"args": [
"run",
"--directory",
"/full/path/to/yokan-board-mcp-project-folder/yokan-board-mcp",
"-m",
"src.main",
"--stdio"
]
}
}
}
Development
Prerequisites
- Python 3.8+
uv(for managing the Python environment)- Access to a running instance of the Yokan API.
Setup
-
Clone the repository:
git clone https://github.com/yokan-board/yokan-board-mcp.git cd yokan-board-mcp -
Create and activate a virtual environment:
uv venv source .venv/bin/activate -
Install the dependencies:
uv sync
Configuration
- Create a
.envfile by copying.env.example:cp .env.example .env - Edit the
.envfile to point to your Yokan API instance:YOKAN_API_BASE_URL=http://your-yokan-api-host:port/api
Running the Server
To start the MCP server for development, run the following command:
uvicorn src.main:app --host localhost --port 8888 --reload
Testing
To run the integration tests, you need to have a running Yokan API instance and a test user. The tests are configured to use the username user and password password.
Make sure your .env file is correctly configured with the YOKAN_API_BASE_URL.
Run the tests using the following command:
make test
Available Tools
The MCP server exposes the following tools for managing a Yokan Kanban board:
| Category | Tools |
|---|---|
| Boards | get_boards, get_board, create_board, update_board, delete_board |
| Columns | create_column, get_columns, update_column, reorder_columns, delete_column, update_column_color |
| Tasks | create_task, create_tasks, get_tasks, update_task, move_task, delete_task |
Usage Examples
You can interact with the MCP server using the fastmcp client library.
Authentication
To use the tools, you first need to obtain a JWT token from your Yokan API instance. You can do this by sending a POST request to the /login endpoint of the Yokan API.
Example using curl:
curl -X POST \
-H "Content-Type: application/json" \
-d '{"username": "your_username", "password": "your_password"}' \
http://localhost:3001/api/v1.1/login
Example: Interacting with the MCP Server
A Python example demonstrating how to use the fastmcp client to interact with the Yokan MCP server can be found in examples/mcp_client.py.
Copyright
Yokan Board MCP is created by: Julian I. Kamil
© Copyright 2025 Julian I. Kamil. All rights reserved.
License
Yokan Board MCP is available under a dual license:
- AGPLv3: Free to use, modify, and distribute under the terms of the GNU Affero General Public License Version 3 (see LICENSE.AGPLv3)
- Commercial License: Available for organizations that wish to use Yokan without AGPLv3's copyleft requirements (see LICENSE.COMMERCIAL)
For information on commercial use licensing, please email: yokan.board@gmail.com
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。