sanban
Enables AI agents to manage kanban boards with tasks, including creating boards, items, moving between columns, and searching.
README
sanban
Simple kanban that just works. No bloat, no login, no SaaS.
JSON-backed boards with a REST API, MCP server, and a dark UI. For devs who want tasks tracked without the overhead.
Screenshots

Quick Start
uv sync
uv tool install .
sanban # http://localhost:8900
The web server runs independently. Agents connect via MCP separately.
Features
- Multiple boards with custom columns
- Drag-and-drop between columns
- Priority, effort, tags, assignees, due dates
- Full-text search and filters
- Markdown in titles and descriptions (code blocks with syntax highlighting)
- Edit and delete buttons on every card
- Keyboard shortcuts (
/search,nnew,eexpand) - Agent-ready via MCP server
Why
- No database — one JSON file per board in
~/.sanban/boards/, easy to diff, commit, back up - No auth — local-first, runs on localhost
- No framework — vanilla JS frontend, Geist font, dark mode
- Multi-board — one server, unlimited boards
REST API
| Method | Endpoint | Description |
|---|---|---|
GET |
/api/boards |
List all boards |
POST |
/api/boards |
Create board { name, columns? } |
GET |
/api/boards/:id |
Get board with items |
DELETE |
/api/boards/:id |
Delete board |
GET |
/api/boards/:id/items |
List items (?q=, ?status=, ?tag=, ?assignee=) |
POST |
/api/boards/:id/items |
Create item |
PATCH |
/api/boards/:id/items/:iid |
Update item |
DELETE |
/api/boards/:id/items/:iid |
Delete item |
GET |
/api/search?q= |
Search across boards |
MCP Server
Agents interact with boards via MCP stdio. This is a separate process from the web server — both read/write the same JSON files.
Agent Config (opencode.json)
{
"mcp": {
"sanban": {
"type": "local",
"command": ["sanban", "--mcp-only"],
"enabled": true
}
}
}
Or running from source:
{
"mcp": {
"sanban": {
"type": "local",
"command": ["uv", "run", "--directory", "/path/to/sanban", "python", "-m", "sanban.server", "--mcp-only"],
"enabled": true
}
}
}
Other agents: Adapt the config format for your CLI agent (Claude Desktop, Cursor, etc.). The command is always
sanban --mcp-only— only the config wrapper changes.
Tools
| Tool | Description |
|---|---|
list_boards |
List all boards |
create_board(name, columns?) |
Create a new board |
get_board(board_id) |
Get board details + items |
create_item(board_id, title, ...) |
Add an item |
update_item(board_id, item_id, ...) |
Update fields |
move_item(board_id, item_id, new_status) |
Move to column |
delete_item(board_id, item_id) |
Remove item |
search(query, board_id?) |
Search across boards |
Run Modes
sanban # web server (REST API + UI) — keep this running
sanban --mcp-only # MCP stdio — for agent config
sanban --rest-only # REST only, no UI
sanban --port 9000 # custom port
Typical setup: run sanban in a terminal (or background it), then add sanban --mcp-only to your agent config. Both use the same ~/.sanban/boards/ data.
Data
Boards live in ~/.sanban/boards/<id>.json. Override with SANBAN_DATA_DIR.
For Agents
See SKILL.md for the full agent reference — API examples, MCP tools, item fields, and keyboard shortcuts.
Tech
Python 3.10+, FastAPI, uvicorn, MCP SDK. No database, no framework, no build step.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.