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Let AI call localhost APIs for local development, testing, and debugging.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "localhostmcp" yet — see the docs or source repo.
Send a GET request to /api/users on my local development server at http://localhost:3000, inspect the status code and response schema, and point out any obvious issues.
A summary of the API call result, including status code, key fields, and any detected issues or debugging suggestions.
Send a POST request to http://localhost:8080/api/login with a test email and password, then determine whether the login flow is working correctly based on the response.
The request result, whether login succeeded, an explanation of returned fields, and possible suggestions for diagnosing endpoint issues.
Call http://127.0.0.1:5000/health and /metrics, summarize service health, response time, and availability, and provide a brief conclusion.
A concise health check report with endpoint status, performance observations, and suggested next troubleshooting steps.
Let AI read, write, search files, and run local commands.
Expose local files, shell, network, and databases to MCP-compatible AI clients.
Run Llama models locally for private, offline AI assistance.
Delegate low-risk tasks to a cheaper model with main-agent review.
Process multimodal content and GUI automation locally with strong privacy and efficiency.
Route coding tasks across local and remote LLMs with benchmarking and code search.