Avito MCP Server: search, chats and listings on Avito

avito-mcp-server

A Python MCP server on Playwright that lets an agent work on Avito from your account: search, item pages, messages to sellers and publishing listings

  • 6 ★ on the repository
  • Last commit
MCP server

Broad access

Why this level

  • The agent writes messages and publishes listings as your Avito account; automating actions may violate platform rules and lead to a ban
  • The avito-data/storageState.json session file keeps account cookies on disk
All reasons and checks
Russian stack

foorsee/avito-mcp-server

Install

Services

Manual install

pip install -r requirements.txt && playwright install chromium

Installs dependencies and the Playwright browser into the virtual environment.

Access and checks

How we review

Broad accessThe tool can change data, run commands or handle secrets.

  • The agent writes messages and publishes listings as your Avito account; automating actions may violate platform rules and lead to a ban
  • The avito-data/storageState.json session file keeps account cookies on disk

This is third-party code. Review the repository files before installing.

What it does

The server launches Chrome, Edge or Chromium through Playwright and works inside your Avito session. You sign in once with a phone number, and the session is saved to avito-data/storageState.json. An agent gets six tools: `avito_search` with city, price and sorting, `avito_get_item_details` with gallery, specs, seller rating and delivery status, `avito_send_message`, `avito_list_chats`, `avito_get_chat_history` and `avito_create_item` for publishing a listing with photos, category and price. It can run in Docker on a headless server, with daemon scripts for macOS and Linux.

Who it is for. Entrepreneurs and developers who search for goods and handle messages on Avito and want to hand the routine to an agent.

Good fit when

  • You want to search for goods and compare item pages with prices, seller rating and delivery
  • An agent should read chats and write to sellers about a listing, for bargaining for example
  • Listings are published in batches with photos, category and price
  • The server has to run on a VPS in Docker with a saved session

Not a fit when

  • You need official access: the project drives a browser and your session, not the Avito API
  • The account must not be exposed to a ban: automating actions may violate platform rules
  • You will not let an agent write messages and publish on your behalf

Example request

Find three bicycle listings on Avito under 30000 rubles and show the sellers' ratings

MCP

Transport
stdio
Authentication
not required

Limitations

The project is unofficial and does not use the Avito API: the server drives a browser in your session, so tools may break when the page layout changes. The agent writes messages and publishes listings on your behalf with no separate confirmation inside the server. The session file holds account cookies and sits on disk. The repository has an interactive captcha script: a human solves it in the browser window. Six stars, one author, last commit in November 2026.

How to disable. Remove the server from your MCP client settings, stop the container with docker compose down and delete the avito-data folder with the session.

FAQ

How does the server sign in?

You sign in once in the browser with a phone number and confirmation, the session is saved to avito-data/storageState.json and the server reuses it.

Does it run on a headless VPS?

Yes, through Docker. Sign in on a computer with a display and copy the avito-data folder to the server.

What if a captcha appears?

Run solve_captcha.py: it opens a browser window, a human solves the captcha, and the session is updated.

Which tools are there?

Six: search, item details, sending a message, chat list, chat history and publishing a listing.

Which Python is required?

Python 3.12 or newer and an installed Chrome, Edge or Chromium; in Docker the browser is already included.

Discussion

No questions or reviews yet.

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README in short

The README covers capabilities, requirements, Python installation, one-time sign-in, Docker deployment and MCP client setup for macOS, Linux and Windows.

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