Tired of syncing between your task tracker, IDE, and markdowns with backlog?

AI project manager
for your agent

For solo builders and tiny teams who ship with AI. Connect via MCP — your agent reads the board, picks up tasks, logs its work, and never loses context between sessions.

Get Early Access See how it works
SP-003 CLOSED · 1 Apr – 11 Apr 2026 · 11 days
SHIPPED
0
MOVED FORWARD
0
COMMITTED
0
COMPLETION
0%
TOTAL TOKENS
0
TOTAL COST
$0
AVG COST / TASK
$0
Scope over time
Task additions across the sprint window
Tasks by module
Final distribution at close time

It's not your fault. But it can be fixed.

Context vanishes between sessions

Every new chat with your agent starts from scratch. Re-explaining what's been done, which decisions were made and why — that's just life with AI. For now.

Your teammates' agents work blind

Two people, two agents, zero shared state. Terminal screenshots in Slack are the only way to stay in sync.

AI costs are a black box

The product is flying, but how many tokens did auth eat? Which feature was cheap, which blew the budget? You won't know until you see the bill.

How it works

Add one MCP connection.
Your agent does the rest.

No setup guides. No config files. Connect and go.

Your agent already knows the project

Kanbang serves your project context, priorities, and working conventions through MCP. Open a new Claude session on Friday and it picks up exactly where Monday left off — no "here's what I've been working on" preamble.

SP-004 ACTIVE Day 4 of 7
Backlog 3
KD-142API rate limiter
backend
KD-145Export CSV report
feature
KD-148Mobile nav layout
frontend
In Progress 2
KD-139Webhook retry logic
backendP1
KD-141Command palette search
frontend
Testing 1
KD-137Org invite flow
auth
Deployed 8
KD-134Token spend panel
frontend
KD-135Sprint dashboard
analytics
+6 more

You never write docs. They write themselves.

Every AI session captures what changed, why, and what it cost. Three weeks later when you wonder "why did we build it this way?" — the answer is already there. No Notion pages. No commit archaeology.

Token spend
AI effort across this project
TOTAL COST
$0
COST / TASK
$0
THIS PERIOD
$0
FORECAST
$0
Daily spend
stacked by operation
By module
last 7 days

Two builders, two agents, one brain

Invite your co-founder. Their AI agent sees the same board yours does. When their agent ships a feature and moves it to testing, your agent knows instantly. No Slack, no standups, no "hey what are you working on?"

Solo builder working with Kanbang dashboard on desktop, laptop, and mobile
Capabilities

Lightweight structure. Zero overhead.

Works with any MCP agent

Claude Code, Codex, Gemini, Cursor — anything that speaks MCP connects to Kanbang out of the box.

Context that survives sessions

Your agent reads the board on startup. No more pasting "here's what we did yesterday" into every new chat.

Know what each feature costs

Token spend per task, per sprint, per project. See where your AI budget actually goes.

Bring a co-founder, not a process

Shared board, shared state. Their agent sees your work, yours sees theirs. No standups required.

Capture from anywhere

Telegram bot, command palette, or just tell your agent. Ideas go to the inbox. Decide what's real later.

Docs that write themselves

Wiki, diagrams, decision logs. Generated from agent activity, not from you opening Notion at midnight.

Your code stays yours

Kanbang never accesses your codebase, your server, or your infrastructure. It's a coordination layer — a shared board between you and your AI agent. Your agent connects via MCP, reads tasks and context, then works in your local environment. Kanbang only sees task titles, descriptions, and status updates.

Think of it as a whiteboard on the wall. Your agent reads what's on it and writes progress back. The whiteboard never opens your laptop.

No code access
No server access
No credentials stored
Just tasks & context
Where this is going

You decide what to build. The agents build it.

Move a card to "In Progress" and your AI agent picks it up automatically — reads the spec, writes the code, logs what it did. When it's done, your co-founder's agent runs the tests.

You're the product owner. The board is the factory floor. The AI agents are the workers. We're not there yet — but every piece of Kanbang is built to make this real.

We built this for ourselves. Now we're sharing it with you.

We build our own product with Claude and were drowning in task chaos, lost context, and invisible costs. Kanbang is the tool we made to fix that for ourselves. It turned out so useful that we decided to open it up for everyone.