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MCP server · AI

Web Agent Protocol

🌐Web Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support

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Scored 9 hours ago · breakdown

About Web Agent Protocol

Web Agent Protocol is an MCP server published by OTA-Tech-AI in the AI category: 🌐Web Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support.

The repository has 507 stars and 92 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/OTA-Tech-AI/web-agent-protocol

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 9 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

wap-replay-tool-1.0.0WAP Replay Tool Desktop 1.0.0 · 1 Jun 2025Your all-in-one **desktop app** for running OTA Web-Agent-Protocol (WAP) *smart* and *exact* replays. This version includes: JSON loader & validator** auto check `exact_replay` / `smart_replay` Inline editor** Exact-replay actions** – edit…

README

Web Agent Protocol

Overview

The Web Agent Protocol (WAP) is a standardized framework designed to enable seamless interaction between users, web agents, and browsers by recording and replaying browser actions. It separates the concerns of action recording and execution, allowing for efficient automation and reusability. The Python SDK for WAP implements the full specification, making it easy to:

  1. Collect user‑interaction data with the OTA‑WAP Chrome extension.
  2. Convert the raw event stream into either exact‑replay or smart‑replay action lists.
  3. Convert recorded actions into MCP servers for reuse by any agent or user
  4. Replay those lists using the WAP-Replay protocol to ensure accurate browser operations.

WAP FULL DEMO

Watch the video

Without WAP

image

WAP Record

image

WAP Replay

image

Example using WAP

image

Setup

Install the dependencies with the following command:

Create a conda env

conda create -n WAP python=3.11

Activate the conda env

conda activate WAP

Install the dependencies

pip install -r requirements.txt

Setup your repo source path:

set PYTHONPATH=C:/path/to/webagentprotocol # for Windows
export PYTHONPATH=/path/to/webagentprotocol # for Linux

Create .env file under the repo root directory with your own API keys:

OPENAI_API_KEY=sk-proj-...
DEEPSEEK_API_KEY=sk-...

Record

WAP record extension

Please refer to OTA‑WAP Chrome Extension to setup action capturer in your Chrome browser.

Start data‑collection server

Run the following command to start the server to collect data from the extension:

python action_collect_server.py

Once the server is up, you can start to record from the page using WAP Chrome extension.

The server listens on http://localhost:4934/action-data by default, please make sure the Host and Port in the extension settings match this server config. Each session will be saved to:

data/YYYYMMDD/taskid/summary_event_<timestamp>.json

An example of the formatted data which you will received in the WAP backend server is like:

{
  "taskId": "MkCAhQsHgXn7YgaK",
  "type": "click",
  "actionTimestamp": 1746325231479,
  "eventTarget": {
    "type": "click",
    "target": "<a ota-use-interactive-target=\"1\" data-ordinal=\"3\" href=\"https://www.allrecipes.com/recipe/68925/cheesy-baked-salmon/\" data-tax-levels=\"\" data-doc-id=\"6592066\" class=\"comp mntl-card-list-card--extendable mntl-universal-card mntl-document-card mntl-card card card--no-image\" id=\"mntl-card-list-card--extendable_3-0\">\n<div class=\"loc card__top\"><div class=\"card__media mntl-image card__media universal-image__container\">...",
    "targetId": "mntl-card-list-card--extendable_3-0",
    "targetClass": "comp mntl-card-list-card--extendable mntl-universal-card mntl-document-card mntl-card card card--no-image"
  },
  "allEvents": {},
  "pageHTMLContent": "<header data-tracking-container=\"true\" data-collapsible=\"true\" class=\"comp header mntl-header mntl-header--magazine mntl-header--open-search-bar mntl-header--myr\" id=\"header_1-0\"><a data-tracking-container=\"true\" id=\"mntl-skip-to-content_1-0\" class=\"mntl-skip-to-content mntl-text-link\" rel=\"nocaes\" href=\"#main\"></a><div class=\"mntl-header__menu-top\">..."
}

Generate replay lists

Mode Command
Exact replay – exactly reproduce every action python wap_replay/generate_exact_replay_list.py --data_dir_path data/<date>/<task_id> --output_dir_path data_processed/exact_replay
Smart replay – condensed goal‑oriented steps python wap_replay/generate_smart_replay_list.py --data_dir_path data/<date>/<task_id> --output_dir_path data_processed/smart_replay

Replace <task_id> with the folder produced by the extension (e.g. em3h6UBDZykz0gnH).

Output structure:

data_processed/smart_replay/
 ├─ subgoals_<task_id>/                     # intermediate prompts & replies
 └─ wap_smart_replay_list_<task_id>.json   # final smart replay list for the agent

data_processed/exact_replay/
 └─ wap_smart_replay_list_<task_id>.json   # final exact replay list for the agent

Replay

python run_replay.py --model-provider openai --wap_replay_list data_processed/exact_replay/wap_exact_replay_list_<task_id>.json --max-concurrent 1

For smart-replay, replace the path with a smart‑replay JSON to test this mode.

Convert to MCP Server

python wap_replay\generate_mcp_server.py --task_id <task_id>

converted MCP servers will be located under mcp_servers folder

Replay with MCP

You would need 2 terminals to replay with MCP. In the first termnial

python wap_service.py

In the second termnial

python mcp_client.py

Then enter your prompt in the second terminal

example: find a top rated keyboard on amazon.ca using smart replay

Replay with our Desktop App

We provide out-of-box desktop app for running replay lists. It is easy to install and you don't need any extra steps for setup and deployments. Visit WAP Replay Tool releases for more details.

Troubleshooting

ModuleNotFoundError – run commands from the project root or export PYTHONPATH=. (set PYTHONPATH=. for Windows).

“no task‑start file” – ensure the extension recorded a full session; the generators require exactly one task-start and one task-finish record.

Acknowledgement

Browser-Use: https://github.com/browser-use/browser-use

MCP: https://github.com/modelcontextprotocol/python-sdk

DOM Extension: https://github.com/kdzwinel/DOMListenerExtension

README fetched from the repository 9 hours ago. The original is authoritative.

Questions

About Web Agent Protocol

How do I install Web Agent Protocol?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Web Agent Protocol safe to use with an AI agent?

Its trust score is 75 out of 100 (good). It passes 5 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Web Agent Protocol still maintained?

The last commit was a year ago and 11 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.