Web Agent Protocol
@OTA-Tech-AI
About Web Agent Protocol
đWeb Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"web-agent-protocol": {
"command": "python",
"args": [
"action_collect_server.py"
]
}
}
}Tools
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Overview
What is Web Agent Protocol?
The Web Agent Protocol (WAP) is a standardized framework for recording and replaying browser actions, enabling seamless interaction between users, web agents, and browsers. It separates action recording from execution, providing a Python SDK to collect raw interaction data, convert it into replayable action lists, and optionally export those lists as MCP servers for reuse by any agent.
How to use Web Agent Protocol?
Install dependencies via pip install -r requirements.txt in a Python 3.11 conda environment, set PYTHONPATH to the project root, and create a .env file with your API keys. To record, install the OTAâWAP Chrome extension, start the dataâcollection server (python action_collect_server.py), and browse normally. Generate replay lists with python wap_replay/generate_exact_replay_list.py (exact) or python wap_replay/generate_smart_replay_list.py (smart), then replay with python run_replay.py --model-provider <name> --wap_replay_list <path>. For MCP integration, run python wap_replay/generate_mcp_server.py, then launch python wap_service.py in one terminal and python mcp_client.py in another.
Key features of Web Agent Protocol
- Record browser interactions via the OTAâWAP Chrome extension
- Generate exactâreplay or smartâreplay action lists from raw events
- Convert recorded actions into MCP servers for reuse by any agent
- Replay action lists using the WAPâReplay protocol
- Provide a desktop app for outâofâbox replay without extra setup
Use cases of Web Agent Protocol
- Automate repetitive browser workflows by recording once and replaying any number of times
- Create goalâoriented smart replays to perform complex multiâstep tasks
- Convert recorded sessions into MCP servers so agents can reuse them without reârecording
- Collect highâfidelity userâinteraction data for training or testing web agents
FAQ from Web Agent Protocol
What is the difference between exact replay and smart replay?
Exact replay precisely reproduces every recorded action (clicks, scrolls, etc.), while smart replay condenses the raw event stream into a smaller set of goalâoriented steps that can adapt to minor page changes.
What are the runtime dependencies for Web Agent Protocol?
The project requires Python 3.11, the packages listed in requirements.txt, and API keys for chosen LLM providers (e.g., OpenAI, DeepSeek) placed in a .env file. A Chrome browser with the OTAâWAP extension is needed for recording.
How do I use the MCP server conversion feature?
Run python wap_replay/generate_mcp_server.py --task_id <task_id>. The generated MCP server will be placed in the mcp_servers folder. Then start wap_service.py in one terminal and mcp_client.py in another to interact with it via prompts.
Where is recorded data stored?
Each recording session is saved under data/YYYYMMDD/taskid/summary_event_<timestamp>.json. The replay lists are stored in data_processed/exact_replay/ and data_processed/smart_replay/.
I get a "no taskâstart file" error when generating replay lists. What does it mean?
The generators require a full recording session that includes exactly one taskâstart and one taskâfinish event. Ensure the Chrome extension captured a complete session before trying to generate the replay lists.
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