Best for
- Web developers debugging and testing complex web applications
- QA engineers automating end-to-end testing
- AI agents needing selector-free browser interaction
The kogiQA MCP Web Browser is a practical browser automation server that enables AI agents to interact with web pages efficiently through natural language and without needing selectors. It is particularly suited for development and testing scenarios, but requires attention to runtime environment and security risks.
Strongest · Setup experience 12/20 Weakest · Reliability 5/20
Static review · not runListed 2026-08-07
Read the FMRS scoring method →Runtime:Node.js 20+
npx kogiqa-mcp@latest.{
"mcpServers": {
"kogiqa-browser": {
"command": "npx",
"args": [
"kogiqa-mcp@latest"
]
}
}
}
Shown for Claude Desktop. Other clients may use a different file or key (VS Code uses "servers") — the configurator below converts it.
{
"servers": {
"kogiqa-browser": {
"command": "npx",
"args": [
"kogiqa-mcp@latest"
]
}
}
}
Goes in your project's .vscode/mcp.json (VS Code uses a "servers" key).
claude mcp add kogiqa-browser -- npx kogiqa-mcp@latest
Run it in a terminal; replace any <…> placeholders with your own values first.
After configuring the client with npx kogiqa-mcp@latest, check that browser_navigate, browser_act, browser_extract, browser_evaluate, browser_console, and browser_screenshot appear in the client's tool list, or ask the agent to navigate to a page and take a screenshot to prove the connection.
Once connected, you can ask your AI assistant things like:
No matching tools
Listed from the project's documentation, not tested by this site.
The kogiQA MCP Web Browser is a Model Context Protocol (MCP) server that provides browser automation capabilities using the kogiQA browser control algorithm. It allows LLMs to interact with web pages through natural language, bypassing the need for screenshots or visually-tuned models, and without requiring selectors, saving time and tokens. It is designed for debugging style issues, automatically fixing console errors, mapping and documenting web app functionality, automatically writing end-to-end tests, and automating exploratory testing.
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Source revision 28326fa00edb Data synced 2026-10-12 Read the FMRS scoring method