Error Logs

What are Error Logs?

Error Logs are a dedicated view for diagnosing tool failures. Each error entry includes the full error message, stack trace, the tool code that was running, the input parameters that triggered the error, and console output before the failure. 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, timeout). Access Error Logs from Observability → Error Logs in the sidebar.

The log list

Each row in the error list shows:

Column	Description
Type	Color-coded level indicator (info, warn, error)
Tool	The tool name that failed
Error Message	Truncated error description extracted from the context
Subdomain	Which server the error occurred on
Time	When the error happened

Log level colours

Level	Indicator	When it’s used
info	Blue dot	Informational logs
warn	Yellow dot	Warnings — tool completed but with issues
error	Red dot	Failures — tool threw or was rejected

Filters

Four independent filters plus a date range:

Filter	Options
Server	Filter by subdomain
Tool	Filter by tool name (cascades based on server)
Type	`info`, `warn`, or `error`
Date Range	Calendar date picker with start and end dates

Error detail

Click any error row to open the full detail modal. The detail view is split into two columns:

Left column — Metadata

Field	Description
Level	Color-coded type chip (info/warn/error)
Tool	The tool that produced the error
Subdomain	The server’s subdomain
Created	Full timestamp of the error

Right column — Diagnostic data

Four expandable sections with all the information needed to reproduce and fix the error: Error context — The primary error information. MCPCore extracts the error message intelligently — parsing JSON responses when available, falling back to raw text:

Error: GitHub API returned 401: Bad credentials

Tool code — The complete JavaScript source code of the tool that was running when the error occurred. This lets you correlate the stack trace line numbers with your actual code. Parameters — The exact params payload that caused the error. Copy these values into the Run panel to reproduce the issue:

{
  "owner": "example",
  "repo": "private-repo"
}

Stack trace — The full call stack at the point of failure (when available):

Error: GitHub API returned 401: Bad credentials
    at tool.js:12:9
    at async MCPCore.executeTool (runtime.js:84:5)

AI-assisted debugging

Each error detail modal includes two AI helper buttons that pre-fill an AI assistant with the full error context:

Ask Claude

Opens Claude with a pre-built prompt that includes:

The platform context (MCPCore)
Tool name and subdomain
Error type and message
The complete tool code
Input parameters that caused the error
Stack trace (if available)

Ask ChatGPT

Opens ChatGPT with the same pre-built error context. Both buttons construct a detailed prompt so the AI has everything needed to diagnose the issue — you don’t need to copy-paste error details manually.

Error types

Type	Cause	What to check
Tool error	Your code threw an uncaught exception	Check the stack trace and tool code
Timeout	Tool execution exceeded 10 seconds	Identify the slow step with `console.time()`
Parameter validation error	The AI passed invalid or missing required parameters	Review parameter definitions
Authentication error	Wrong API key, expired token, or missing credentials	Verify secret values
Sandbox error	An internal error in the MCPCore execution environment	Contact support if persistent

Common errors and fixes

`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.

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.

`JSON.parse(): Unexpected token`

Your code called JSON.parse() on a non-JSON response body. Fix: Add a status 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);

Timeout (10s exceeded)

The tool took longer than 10 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
Large result set — add LIMIT to SQL queries or paginate

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.

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.

Getting Started

MCP Servers

Tools

Observability

Connect AI Clients

What are Error Logs?

The log list

Log level colours

Filters

Error detail

Left column — Metadata

Right column — Diagnostic data

AI-assisted debugging

Ask Claude

Ask ChatGPT

Error types

Common errors and fixes

`env.MY_KEY is undefined`

HTTP 401 / 403 from external API

`JSON.parse(): Unexpected token`

Timeout (10s exceeded)

Parameter validation error

Setting up alerts

​What are Error Logs?

​The log list

​Log level colours

​Filters

​Error detail

​Left column — Metadata

​Right column — Diagnostic data

​AI-assisted debugging

​Ask Claude

​Ask ChatGPT

​Error types

​Common errors and fixes

​env.MY_KEY is undefined

​HTTP 401 / 403 from external API

​JSON.parse(): Unexpected token

​Timeout (10s exceeded)

​Parameter validation error

​Setting up alerts

What are Error Logs?

The log list

Log level colours

Filters

Error detail

Left column — Metadata

Right column — Diagnostic data

AI-assisted debugging

Ask Claude

Ask ChatGPT

Error types

Common errors and fixes

`env.MY_KEY is undefined`

HTTP 401 / 403 from external API

`JSON.parse(): Unexpected token`

Timeout (10s exceeded)

Parameter validation error

Setting up alerts