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What are Error Logs?

Error Logs are a filtered view of your Traffic Logs that shows only the requests that resulted in an error. Instead of scanning through all requests, you get a focused list of failures — with everything you need to reproduce and fix the problem. A request is classified as an error when your tool code throws an uncaught exception, or when MCPCore rejects the request before your code runs (e.g. invalid parameters, authentication failure). Access Error Logs from Observability → Error Logs in the sidebar.
Error Logs list showing failed requests with error type labels

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Error types

TypeCause
Tool errorYour code threw an uncaught exception
TimeoutTool execution exceeded 30 seconds
Parameter validation errorThe AI passed invalid or missing required parameters
Authentication errorThe request failed the server’s security check (wrong API key, expired token, etc.)
Sandbox errorAn internal error in the MCPCore execution environment

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Error detail

Click any error row to open the full detail view:
Error log detail showing error message, stack trace, input params, and console logs

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Error message

The exception message thrown by your code, or the MCPCore-generated error for validation/auth failures. 
Error: GitHub API returned 401: Bad credentials
    at Object.<anonymous> (tool.js:12:9)

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Stack trace

The full call stack at the point of failure. Use this to identify the exact line in your tool code that threw the error. 
Error: GitHub API returned 401: Bad credentials
    at tool.js:12:9
    at async MCPCore.executeTool (runtime.js:84:5)

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Input parameters

The params payload that caused the error — useful for reproducing the issue in the Run panel. 
{
  "owner": "example",
  "repo":  "private-repo"
}

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Console output

Any console.* calls your code made before the failure — often the most useful debugging signal. 
[INFO]  Fetching repo: example/private-repo
[ERROR] GitHub API returned status 401

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Common errors and fixes

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env.MY_KEY is undefined

Your code references a secret that doesn’t exist on this server. Fix: Go to the Secrets tab, check that the secret exists with exactly the name used in code (case-sensitive), and add it if missing.

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HTTP 401 / 403 from external API

Your credentials are wrong, expired, or don’t have permission for the requested resource. Fix: Verify the secret value in the dashboard (you can delete and re-add it with the correct value), and check the permission scopes for the API key in the external service’s settings.

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JSON.parse(): Unexpected token

Your code called JSON.parse() on a non-JSON response body. Fix: Add a check before parsing: 
const body = res.body();
if (res.status() !== 200) {
  console.error("Non-200 response:", res.status(), body);
  throw new Error(`API error ${res.status()}: ${body.slice(0, 200)}`);
}
const data = JSON.parse(body);

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Timeout (30s exceeded)

The tool took longer than 30 seconds to complete. Fix: Identify the slow step using console.time() / console.timeEnd(). Common causes:
  • Database query without an index on the filter column
  • External API with high latency — add a timeout to sdk.http()
  • Large result set — add LIMIT to SQL queries or paginate

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Parameter validation error

The AI passed invalid input — wrong type, missing required field, or value outside expected range. Fix: Review your parameter definitions and strengthen the descriptions so the AI knows exactly what to pass. For optional parameters, set sensible default values.

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Setting up alerts

Error rate alerts via email and webhook are coming soon. Until then, monitor the Error Logs page or use the Analytics error rate chart.