How karst works

The problem

AI dev tools read your code blind.

Ask Cursor or a custom agent “how does checkout work?” and it dumps tens of thousands of tokens of vaguely-related files into the model — every single time. You can’t see what it loaded, you can’t scope it, and the bill arrives at the end of the month.

✕Bill shock. A single question can burn 30k+ input tokens. Usage-based pricing turns that into real money, fast.
✕Black-box context. When the answer is wrong you can’t tell if it was the model or the context it never saw.
✕No blast radius. Nothing tells you what else breaks when you change a function.

agent · “how does checkout work?” context window

42,000 tokens loaded · mostly irrelevant $0.13 / question

The fix, in four moves

Give the model a map before it reads

Click a step — or just watch. This is exactly what the engine does to your repo today.

byfoods / src / orders / orders.ts — karst

▾ src

▾ auth

users.ts

▾ billing

stripe.ts

▾ orders

orders.ts

cart.ts

// imports
import { getUser } from '../auth/users';
import { charge } from '../billing/stripe';

chunk · checkout()export async function checkout(cartId: string) {
  const cart = await loadCart(cartId);
  const user = await getUser(cart.userId);
  const total = cart.items.reduce((s, i) => s + i.price, 0);
  return charge(user, total);
}

chunk · loadCart()async function loadCart(id: string) {
  return db.carts.findById(id);
}

Files that change & call together → one named pack

ordersorders.ts · cart.ts · ~2 chunks

authusers.ts · login.ts

billingstripe.ts

› how does checkout work? — packs: orders

checkout() loads the cart, fetches the buyer via getUser() [orders/orders.ts:5], sums item prices, then calls charge() [billing/stripe.ts].

~3,800 tok · $0.019 vs $0.13 unscoped — shown before the call

01 · INDEX

Parse into chunks

Tree-sitter splits every function, class and method into a real chunk — never blind line-windows.

02 · GRAPH

Map who calls who

A knowledge graph of calls & imports. Now “what breaks if I change this?” is a graph walk, not a guess.

03 · PACK

Group into named packs

Related files become attachable packs — auth, billing, orders. The atomic unit of context.

04 · ASK

Load only what matters

A question loads only its pack. 60% fewer tokens, every answer cited, the cost shown before you spend it.

What actually changes

Same question. One-seventh the cost.

WITHOUT karst

$0.13

• 42,000 tokens dumped per question
• You can’t see what was loaded
• No citations — trust it or don’t
• No idea what a change will break

WITH karst

$0.019

• ~3,800 tokens — only the relevant pack
• You see (and pin) exactly what loads
• Every claim cited to file:line
• karst impact lists the blast radius

Measured on Byfoods — a real 246-file NestJS + Next.js repo: 906 chunks, re-index 343s → 2.3s.

Straight about what’s built

Does it solve your problem? Here’s the honest map.

LIVE TODAY

✓ MCP server — plug into Cursor & Claude Desktop
✓ AST chunking across 6 languages
✓ Call/import graph + impact analysis
✓ Pack-scoped retrieval & cost meter
✓ Incremental indexing + embedding cache
✓ Diff code review with citations

COMING NEXT

◷ Hosted indexing (no local daemon)
◷ Team-shared pack library
◷ GitHub PR review bot
◷ Published to PyPI & the MCP registry

The engine and the MCP server that exposes it to Cursor & Claude Desktop are both real and tested — every number on this page is measured, not promised. What’s left is distribution: a one-line install once it’s on PyPI. We’d rather tell you exactly where the line is than pretend.

How karst works

AI dev tools read your code blind.

Give the model a map before it reads

Same question. One-seventh the cost.

Does it solve your problem? Here’s the honest map.

Want it pointed at your repo?