Loading…
Open-source, self-hosted testing: describe a test in plain English and an AI agent runs it in a real browser or against your API, chatbot, MCP server or A2A agent. You get pass/fail or a score with steps, screenshots and a plain-English explanation, on Anthropic, OpenAI, Gemini, OpenRouter, Groq or local Ollama.
Plainwright is an MCP server entry in ChatHome Skills, sourced from GitHub MCP Search and scored 40/100. Open-source, self-hosted testing: describe a test in plain English and an AI agent runs it in a real browser or against your API, chatbot, MCP server or A2A age. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding Plainwright to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
git clone https://github.com/SaiBolisetty/Plainwright.gitReview the upstream source before running this command.
Executes inline Python code, which can hide malicious behavior in a compact payload.
python -c "Dispute this flag?Scan coverage: Install metadata and repository README.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
{
"fullName": "SaiBolisetty/Plainwright"
}Open-source, self-hosted testing: describe a test in plain English and an AI agent runs it in a real browser or against your API, chatbot, MCP server or A2A agent. You get pass/fail or a score with steps, screenshots and a plain-English explanation, on Anthropic, OpenAI, Gemini, OpenRouter, Groq or local Ollama.