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ATR: Automation for Token Reduction

ATR: Automation for Token Reduction

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github.com/JacobBhatt12AI & Agents2Updated 2d ago

About ATR: Automation for Token Reduction

ATR is a local proxy between AI apps and MCP servers that reduces tool context by finding tools on demand and shrinking results. It is intended for users working with many tools or large outputs, while retaining full results for later queries.

Key features

  1. 01Searches for tools relevant to a task
  2. 02Shrinks results while retaining full content
  3. 03Retrieves selected parts of trimmed results
  4. 04Separates read-only and changing calls
  5. 05Provides code reading, search, and run tools

Use cases

  1. 01Trim GitHub lists or browser page results
  2. 02Show only failing tests from test output
  3. 03Extract relevant content from large logs or diffs

MCP support

ATR connects AI apps to downstream MCP servers as a proxy, exposing tools for searching, reading, and calling them to clients. It also offers an MCP HTTP serving mode.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"jacobbhatt12-atr": {
"command": "uvx",
"args": [
"atr-mcp"
]
}
}
}
Run commanduvx atr-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypiatr-mcp1.0.0

Tools

10

Saved tool list · updated 1d ago

ParameterTypeRequiredDescription
kintegerNoHow many tools (default 5).
querystringYesWhat you want to do, in a few words.
detailbooleanNoAlso return the parameter schemas.

Details

From the project README

ATR: Automation for Token Reduction

ATR makes your AI use fewer tokens when it works with tools. Fewer tokens means lower bills and fewer "usage limit reached" messages.

It works with Claude Code, Codex, Claude Desktop, Cursor, Windsurf, claude.ai and ChatGPT. It's free and runs on your own computer.

ATR demo: 1,000 GitHub issues go from 329,732 tokens to 1,442, and the tool list from 12,376 to 1,438

The problem

When an AI uses tools (GitHub, a browser, a database, your test runner), two things waste tokens:

  1. Every tool's instructions are sent on every message, even tools the AI never uses. Ten MCP servers can mean 10,000+ tokens before you've typed anything.
  2. Tool results are huge. A list of GitHub issues, a web page or a test run can be tens of thousands of tokens, and all of it goes into the chat.

What ATR does

ATR sits between your AI app and your tools:

  • It hides the tool list. The AI sees a few small ATR tools and searches for the tool it needs when it needs it.
  • It shrinks results. Before the AI sees a result, ATR removes the noise and keeps what matters. A failing test run keeps the failures and drops the passing tests. A web page keeps its text and links and drops the layout.
  • Nothing is lost. When ATR cuts something, it keeps the full result, and the AI can ask for any part of it.
  Your AI app (Claude Code, Codex, Claude Desktop, …)
          │  sees a few small ATR tools instead of every tool
          ▼
        ATR  ← finds the right tool, runs it, shrinks the result
          │
          ▼
  Your MCP servers (GitHub, Playwright, Postgres, Slack, …)

Get started

You need Python 3.11 or newer.

pip install atr-mcp
atr setup

atr setup finds the AI apps on your computer, shows you what it will change, and asks first. Then it:

  1. moves your MCP servers behind ATR, and
  2. adds ATR to each app.

Restart your apps and you're done.

CommandWhat it does
atr setup --dry-runShows the plan without changing anything
atr setup --undoPuts every app back exactly how it was
pip install --upgrade atr-mcpUpdates ATR

Every file atr setup changes also gets a backup copy (.atr-backup).

Just want to try it?

The demo connects a fake server with 50 tools (GitHub, Slack, logs, a database). Nothing leaves your computer.

claude mcp add atr -- atr serve --demo        # Claude Code
codex mcp add atr -- atr serve --demo         # Codex

Ask your AI to "list the open GitHub issues", then "show ATR stats" to see how many tokens it saved.


How much it saves

Live tests

We gave AI agents the same browser task with and without ATR: open Hacker News, click "new", then open a GitHub issues page. Each setup ran 3 times, and every answer was correct.

AgentWithout ATRWith ATR
Claude Code$0.237 per task, 13 turns$0.110 per task, 10 turns (54% cheaper)
Codex84k tokens (33k at full price)134k tokens (18k at full price)

Codex is mixed: with ATR it sends about half as many full-price tokens, but more tokens overall.

Single results

What the AI receives, in tokens, measured with python -m benchmarks.bench_atr:

ResultWithout ATRWith ATRSaved
1,000 GitHub issues429,20387999.8%
2,000-line server log61,07220899.7%
git diff with a lockfile change22,29420799.1%
Web page in a browser (Hacker News)12,0234,04666%
50 tools' instructions, on every message12,0561,50887.5%
pytest -v, 303 tests, 3 failing6,68567590%
pip install, 60 packages5,97769788%

In each case, the parts that matter are kept: errors, failing tests, changed code lines, page text and links.

When ATR helps, and when it doesn't
  • Helps most: you use MCP servers that return big results, like GitHub, browsers (Playwright), databases, logs or web pages.
  • Helps a little: plain coding in Claude Code or Codex with no MCP servers. Those apps already trim their own commands, so in our test ATR made no difference there.
  • Can't help: your chat history and the AI's own replies. An MCP server only sees tool calls, never the conversation.

ATR's tools

The AI uses these. You don't need to call them yourself.

For your MCP servers

ToolWhat it does
atr_find_toolsSearches all your servers' tools and returns the few that fit the task
atr_readRuns a tool that only reads, and shrinks the result
atr_callRuns a tool that changes something (your app can ask you first)
atr_queryReads more of a result that was cut, such as one page, one field or a search

For coding

ToolInstead of
atr_repo_mapOpening files one by one to learn a project
atr_search_codePages of search results
atr_read_fileReading a whole file to see one function. It also says "unchanged" if the AI reads the same part twice
atr_diffA git diff full of lockfiles
atr_runThousands of lines of test or build output
atr_statsShows how many tokens ATR has saved

Safety

  • Secrets are never read, searched or shown, including .env files, private keys, cloud credentials, and files named like api_keys.json. This also applies to tools behind ATR and to atr_diff.
  • Reading and changing are separate. Tools that only read go through atr_read. Anything that changes something goes through atr_call, so your app can ask you before it runs. atr_run (shell commands) always asks.
  • Files stay in allowed folders. File tools only see the folders listed in your settings.

Using ATR in claude.ai or ChatGPT

These apps can only reach servers on the internet, so ATR needs a public link.

pip install "atr-mcp[http]"
atr serve --http                               # prints a link with a secret in it
tailscale funnel --bg 8789                     # a permanent public https link (or: cloudflared tunnel --url http://127.0.0.1:8789)

Add https://<your-link>/mcp/<secret> as a connector:

  • claude.ai: Settings → Connectors → Add custom connector (no sign-in)
  • ChatGPT: Settings → Apps & Connectors → developer mode → create a connector (no sign-in)

Keep the link private. Anyone who has it can use your tools. File reading and shell commands are off over the internet unless you turn them on with --read-files and --allow-run. To change the secret, delete ~/.atr/http_token.


Settings

atr setup writes these for you. You can also edit ~/.atr/config.json yourself:

{
  "servers": {                          // the MCP servers ATR runs for you
    "github": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-github"] }
  },
  "budget": 1500,                       // most tokens one result may use
  "level": 2,                           // 1 = keep almost everything, 3 = shrink hard
  "pin": ["github__create_issue"],      // tools to always show (skips the search step)
  "read_only": ["github__list_*"],      // tools that only read, if a server doesn't say so itself
  "read_roots": ["~"]                   // folders the file tools may open
}

More

No MCP at all? atr compress shrinks a file or your clipboard before you paste it into any chat:

atr compress dump.json --copy
pbpaste | atr compress --copy

Set up by hand: atr init writes the settings file, and atr snippet prints the entry to add to your app's MCP config.

"No module named 'atr'" on macOS: run chflags nohidden .venv*/lib/python*/site-packages/*.pth, or use the entry from atr snippet.

Limits:

  • Online servers that need a sign-in (OAuth) can't go behind ATR yet, so atr setup leaves them in your app.
  • ATR lowers what each message costs. It doesn't change your plan's limits.

For developers

git clone https://github.com/JacobBhatt12/atr && cd atr
pip install -e ".[dev]"
python -m pytest atr/tests -c /dev/null       # 44 tests
python -m benchmarks.bench_atr                # the savings table above
FileWhat's in it
atr/server.pyThe MCP server your app talks to
atr/remote.pyThe same server over the internet (atr serve --http)
atr/downstream.pyTalks to the MCP servers behind ATR
atr/compress.pyShrinks results
atr/stash.pyKeeps full results for atr_query
atr/router.pyTool search
atr/code.pyCoding tools
atr/setup.pyatr setup

Next up: remembering repeated tool calls so the same result isn't sent twice, sign-in support for online servers, and a small local model that summarizes long text when cutting would lose meaning.

License: MIT

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.