Integrates with GitHub for version control, project hosting, and contribution workflow, with references to related GitHub repositories.
Integrates with Jest for testing the MCP server, with scripts for running tests, watch mode, and generating coverage reports.
Enables installation and distribution of the KnBn MCP server through the npm registry, with support for development workflows using npm scripts.
Built with TypeScript, providing type-safe interactions with kanban functionality and requiring compilation to JavaScript before use.
KnBn MCP Server
A Model Context Protocol (MCP) server that provides AI assistants with structured access to kanban board functionality. Built on top of the KnBn CLI tool, this server exposes kanban operations through MCP tools and resources.
Overview
KnBn MCP Server enables AI assistants to interact with kanban boards programmatically using the standardized MCP protocol. It provides three main interaction methods:
- MCP Tools: Interactive operations for creating, updating, and managing boards, tasks, columns, labels, and sprints
- MCP Resources: Read-only access to board data with structured URI patterns
- CLI Integration: Built on the proven KnBn CLI for reliable board operations
Features
- Board Management: Create, list, and migrate kanban boards
- Task Operations: Full CRUD operations including batch updates
- Column Management: Create, update, remove, and list board columns
- Label System: Add, update, remove, and list task labels with colors
- Sprint Management: Create and manage development sprints
- Resource Access: Read-only data access via MCP resources
- Migration Support: Upgrade board files to latest format versions
Installation
As MCP Server
- Install the package:
- Configure in your MCP client (e.g., Claude Desktop):
For Development
- Clone the repository:
- Install dependencies:
- Build the project:
- Run tests:
Usage
MCP Tools
The server provides organized tool categories:
Board Tools
list_boards
- List all .knbn board filesget_board
- Get complete board contentscreate_board
- Create new board with name and descriptionmigrate
- Migrate board files to latest version
Task Tools
create_task
- Create task with title, description, priority, story pointsget_task
- Get task details by IDlist_tasks
- List/filter tasks by column, label, priority, sprintupdate_task
- Update task propertiesupdate_tasks_batch
- Update multiple tasks efficiently
Column Tools
create_column
- Add new column at specified positionlist_columns
- List all columns with optional task countsupdate_column
- Rename existing columnremove_column
- Delete column
Label Tools
add_label
- Create label with name and colorlist_labels
- List all available labelsupdate_label
- Modify label name or colorremove_label
- Delete label from board
Sprint Tools
add_sprint
- Create sprint with dates, capacity, descriptionlist_sprints
- List sprints filtered by statusupdate_sprint
- Modify sprint propertiesremove_sprint
- Delete sprint
MCP Resources
Access board data through structured URIs:
knbn://boards
- List of all board filesknbn://board/{filename}
- Complete board dataknbn://board/{filename}/summary
- Board summary with metricsknbn://board/{filename}/tasks
- All tasks from a board
Example Usage
Development
Scripts
npm run build
- Compile TypeScript to JavaScriptnpm test
- Run Jest testsnpm run test:watch
- Run tests in watch modenpm run test:coverage
- Generate coverage report
Architecture
Testing
Tests are located in tests/
with fixtures in tests/fixtures/
. Run the test suite:
Generate coverage report:
Board File Format
Board data is stored in .knbn
files using a structured format. The MCP server handles all file operations automatically, but you can also interact with these files directly using the KnBn CLI.
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests for new functionality
- Run the test suite
- Submit a pull request
License
MIT License - see LICENSE for details.
Related Projects
- KnBn CLI - Command-line kanban tool
- KnBn Web - Web interface for KnBn boards
- Model Context Protocol - Protocol specification
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A Model Context Protocol server that provides AI assistants with structured access to kanban board functionality for managing tasks, columns, labels, and sprints.
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