How it works

Your AI stops calling tools one by one.
It writes the program.

Delta MCP is a free app that sits between your AI apps and their MCP servers. Your AI writes each task as one short program; Delta MCP checks it, makes the fewest calls, all or nothing, reads the result back and keeps it in Activity.

Updated 8 October 2026 · 8 minutes to read

A task, as your AI writes it · from Delta MCP’s tests

// delta { code }: one call for the whole task
const t = await tickets.ticket.get("T-1");
t.status = "closed";
t.labels.push("late");
t.comments.push({ body: "Closed: fixed in 2.3" });
return t.title;

// Delta MCP turns it into the fewest calls:
// update_ticket, then add_comment, all or nothing

Today, your AI does three jobs at once

With MCP as it is used today, the model carries out every step itself, one by one, and pays for each in tokens.

The processor

One full inference for every step: read, decide, call one tool, wait, read again.

The bus

Every piece of data passed from one step to the next goes through its context, and is paid for again at each step.

The memory

Everything must fit in its window: every tool definition, every result, the whole conversation.

55,000

tokens of tool definitions before the first word, for 58 tools on 5 servers.

Anthropic, Nov 2025

30–50

tools: past this, the model starts choosing the wrong one.

Anthropic, tool search docs

52.6%

first-try success for the best model on 127 real MCP tasks, with 17.4 tool calls per task on average.

MCPMark, ICLR 2026

128

tools: the most VS Code accepts at once.

VS Code, issue #290356

A developer doesn’t click every button

Coding agents are good because code has a compiler, tests and version control. Delta MCP gives your AI the same around your services: types to write against, checks before anything runs, and a history you can roll back.

Aspect	Direct MCP calls	Through Delta MCP
Who decides the calls	The model, one per turn	Delta MCP, from the whole program
What the model loads	Every tool’s definition, every time	Three tools, and typed collections for each server
Data between steps	Goes through the model’s context	Stays in the program
Mistakes	Found one at a time, after calls were made	All found before the first call, each with its fix
A failure halfway	Leaves the work half done	All or nothing
Afterwards	The model says it worked	Delta MCP reads it back and compares
History	None	Activity: every change before and after, and Undo
Your tools	All there	All still there: 152 of 152 on the largest server we tried

One door between your AI and your servers

Your AI apps talk to one MCP server, Delta MCP, on your computer. Delta MCP talks to your servers exactly as they are: nothing to change, nothing to rewrite.

How one task runs

Write

Your AI writes the whole task as one short program.

Check

Delta MCP checks it before the first call and returns every error at once, each with its fix.

Plan

It works out the fewest calls the server needs, in the right order.

Apply

It makes them all, or none. What the server can’t do is refused up front.

Read back

It reads the result back, records it in Activity, and keeps what it takes to undo.

Checked before the first call

t.labls.push("late");

✗ no field "labls" — did you mean labels?
  every error at once, each with its fix;
  nothing was sent to the server

The plan · an illustration

d_… · 2 calls, all or nothing
1  update_ticket   T-1  status=closed  labels+late
2  add_comment     T-1  "Closed: fixed in 2.3"

Applied · read back ✓ · undo: delta_apply { undo: "d_…" }

Deep objects, as short text

Some objects nest: a test has steps, a step has actions, an action has checks. Your AI reads such an object as a few lines of text and rewrites it; Delta MCP aligns the lines, keeps each one’s identity, and turns the difference into the fewest calls.

Delta MCP uses this text form only when writing it back changes nothing on the server.

A document · from Delta MCP’s tests

// read "T-1"
ticket T-1: Login broken
  status=open

// your AI rewrites it
ticket T-1: Login broken
  status=closed labels=late
comment "Closed: fixed in 2.3"

Applied d… · 1 ticket(s) · 2 call(s) · read back: as written ✓

Nothing is lost

Every tool of every server stays declared and callable as it is, by name. On Cerberus, a test platform with 152 tools, all 152 are there, in a starting context about 17 times smaller (an estimate, in characters).

Any original tool, by its name · from a real run, 5 Oct

await cerberus.cerberus_test_folder_create({
  testFolder: "RT-p7-cerberus-s1",
  description: "Tests automationexercise.com (API + front)"
});
await world.commit();

// 152 of 152 Cerberus tools, the same way

Live, when the next step depends on the last

A browser can’t be planned in advance: what to click depends on what the page shows. For that, the program runs live, one action at a time. Objects it changes are still applied together at the end, and can be undone.

Live mode · an illustration

await web.goto("https://shop.test/form");
await web.fill({ Name: "Ana" });
await web.press("Create");
return "done";

You decide how much it does alone

For each connector: change on its own (the suggestion: everything shows in Activity), ask before deleting or sending, ask before every change, or read only.

Money that leaves is apart: paying, buying, refunding, transferring and trading ask you on a card by default, and your AI can never loosen that rule.

Change on its own Suggested

Ask before deleting or sending

Ask before every change

Read only

Code execution with MCP, ready-made

Anthropic and Cloudflare have both shown that agents use MCP far better by writing code than by calling tools, and both name the price: a safe place to run that code, and the checks around it. Delta MCP is that, ready-made, for every MCP server you already use, on your computer.

One workflow went “from 150,000 tokens to 2,000 tokens”, a 98.7% saving, once the agent wrote code instead of calling tools.

Anthropic, Code execution with MCP, 4 November 2025

More than 2,500 API endpoints exposed to an agent in about 1,000 tokens, by giving it a typed SDK and asking it to write code.

Cloudflare, Code Mode, 20 February 2026

What it doesn’t do

Save on every task. A single one-step question costs more, because your AI reads Delta MCP’s description. The gain is on tasks with several steps.

Undo everything. A message sent or money gone can’t be taken back, and a deleted item comes back as a new copy. Delta MCP says which, before and after.

Stop a determined AI. It protects you from your AI’s mistakes; your AI still acts with your rights. Measured so far with Claude Code only.

Keep reading

How to reduce MCP token usage, and why MCP burns tokens

How to reduce MCP token usage: measure it with /context, see the two costs (tool menu and round trips), and compare every fix, Tool Search included.
MCP vs CLI for AI agents: where the token bill comes from

MCP or CLI for your AI agent? What each costs in tokens, what the measurements show, when a CLI wins, when MCP does, and where code beats both.

Your AI stops calling tools one by one.
It writes the program.

Today, your AI does three jobs at once

The processor

The bus

The memory

A developer doesn’t click every button

One door between your AI and your servers

How one task runs

Write

Check

Plan

Apply

Read back

Deep objects, as short text

Nothing is lost

Live, when the next step depends on the last

You decide how much it does alone

Code execution with MCP, ready-made

What it doesn’t do

Keep reading

See it on your own tasks

Delta MCP is almost here

Your AI stops calling tools one by one.It writes the program.

Today, your AI does three jobs at once

The processor

The bus

The memory

A developer doesn’t click every button

One door between your AI and your servers

How one task runs

Write

Check

Plan

Apply

Read back

Deep objects, as short text

Nothing is lost

Live, when the next step depends on the last

You decide how much it does alone

Code execution with MCP, ready-made

What it doesn’t do

Keep reading

See it on your own tasks

Your AI stops calling tools one by one.
It writes the program.