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Let AI coding agents read live web app logs, errors, and requests.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "console-stream-mcp" yet — see the docs or source repo.
After connecting to console-stream-mcp, read the current page's live console errors and warnings, summarize them in time order, and identify the most likely root cause with fix suggestions.
A time-ordered error summary with likely causes, impact, and recommended fixes.
Use console-stream-mcp to inspect the page's recent failed network requests, list the failed endpoints and status details, and determine whether the issue is in the frontend call or the server.
A list of failed requests and a brief analysis of where the problem likely originates.
Continuously read this web application's live console output and network request changes, and immediately summarize anomalies with key points to watch.
A monitoring summary of live logs and request changes, with suspicious anomalies highlighted.
During web app debugging, developers can let AI read live console logs, errors, and network requests without manually pasting them into chat. This helps identify frontend issues and API call problems faster.
During page testing, teams can use this tool to let AI observe runtime console and request behavior, helping summarize issues and organize debugging clues.
It enables AI coding agents to access live console logs, error messages, and network requests from web applications through a local WebSocket connection. The description specifically says this works without manually copying data into chat.
According to the description, it provides access through a local WebSocket connection. For more specific installation or runtime requirements, see the source repository.
Its key difference is that AI can directly read live logs, errors, and network requests instead of relying on manual copy-paste. This makes it better suited for ongoing debugging and observing dynamic page behavior.
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