ATR (Automation for Token Reduction)

Proxy MCP que economiza tokens. Oculta as listas de ferramentas dos seus servidores MCP por trás de uma ferramenta de busca e reduz resultados extensos de ferramentas (GitHub, Playwright, logs, saída de testes), mantendo o resultado completo disponível sob demanda. Configuração com um único comando para Claude Code, Codex, Claude Desktop e Cursor.

Documentação

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. Run it on your own computer, or add the hosted connector to a chatbot in a minute, with no install: https://atr-mcp.vercel.app (connector link: https://atr-mcp.vercel.app/mcp).

ATR in a chatbot: GitHub issues, web search, PDFs, places and weather, with 30 issues cut from 53,724 tokens to 419 and a PDF from 9,962 to 263

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.
 
 
 

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.

In the free hosted connector

ToolWhat it does
atr_fetchReads live web pages, PDFs, Office documents and JSON as compact text
atr_searchSearches the web with DuckDuckGo, Bing and Brave at once and returns one short merged list (about 60 tokens a result); no API key needed
atr_placesFinds local businesses and places with free OpenStreetMap data; no API key needed
atr_siteInspects a website or searches its public sitemap and navigation
atr_weatherGets current weather and up to seven forecast days; no API key needed
atr_queryRetrieves more from a large result ATR kept
atr_statsShows how many tokens ATR has saved

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

No install: add the hosted connector https://atr-mcp.vercel.app/mcp the same way (Settings → Connectors → Add custom connector, no sign-in). Then do the one-time step below.

Tell your chatbot to use it. Chatbots pick their own built-in web tools first, and in tests Claude never chose ATR by itself. Add this once under Settings → Profile → personal preferences (or in a Project's instructions):

When I ask you to search the web or read a link, use atr_search and atr_fetch instead of the built-in web tools.

Or skip the setup and ask your question and add "use atr", like "What is the latest on the MCP spec? Use atr." (or "use atr_search", "use atr_fetch"). This is only needed for the web tools. Tools you put behind ATR (GitHub, for example) are found by name.

For your own tools behind ATR, you need a link of your own:

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