GitHub Copilot Status Check Commands and Diagnostics Guide

When GitHub Copilot fails to provide suggestions, the root cause is rarely a service outage, but rather a network blockage between the local environment and GitHub servers. Rather than checking a public status page, developers can use command line tools to trace the path and pinpoint where the connection drops. The primary tool for this is the terminal, where standard network diagnostics can determine if GitHub's backend endpoints are reachable.

Before running complex connection tests, you should verify that your local DNS server resolves the required hostnames. You can run the name server lookup command:

nslookup copilot-proxy.githubusercontent.com

If the DNS lookup fails, your local network is blocking the hostname resolution. If it resolves to an IP address, you can proceed to test the HTTP connection.

To check if your network allows connection to GitHub's Copilot services, run a verbose request using the command line transfer utility curl:

curl --verbose https://copilot-proxy.githubusercontent.com/_ping

A successful connection will return an HTTP 200 response with the text 'OK' or a simple ping confirmation. The verbose flag prints the entire connection transaction, showing the DNS lookup, the local socket connection, and the TLS handshake. When the handshake succeeds, the terminal displays details about the server certificate and the secure connection cipher.

If your development machine operates behind a corporate HTTP proxy, you can test if the request succeeds through that proxy by using the proxy configuration flag:

curl --verbose -x http://YOUR-PROXY-URL:PORT -i -L https://copilot-proxy.githubusercontent.com/_ping

Replace the placeholder values with your organization's proxy server address and port. The tool respects standard terminal environment variables such as HTTPS_PROXY, https_proxy, HTTP_PROXY, and http_proxy if they are defined in your shell profile.

To dynamically check which domains your local firewall needs to allow for GitHub Copilot, you can query GitHub's meta API using the GitHub CLI:

gh api meta -q '.domains | .website, .copilot'

This command returns the list of wildcard domains required for authentication, code completions, and chat interactions. You must ensure your network allowlist includes these domains, along with the apex domain github.com, to prevent connection timeouts.

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More on this subject: GitHub Copilot (89 guides)

VS Code's Collect Diagnostics utility compiles connection telemetry, IDE settings, and logs in a single click, providing a complete snapshot of the local environment. When troubleshooting GitHub Copilot in Visual Studio Code, this command-palette utility is the fastest way to gather telemetry without manually hunting for logs in system directories.

Visual Studio Code version 1.99 or later introduces support for Model Context Protocol (MCP) servers in agent mode. This enables the editor assistant to connect directly to local tools and remote developer platforms. To configure custom tools, developers specify the connection details in the editor settings. GitHub officially deprecated and sunset its legacy GitHub App-based Copilot Extensions on November 10, 2025, in favor of the Model Context Protocol. This transition ensures that integrations use open standards rather than platform-specific apps.

To run the diagnostic tool, follow these steps:

1. Open the Command Palette in Visual Studio Code using the keyboard shortcut Shift+Command+P on macOS or Ctrl+Shift+P on Windows and Linux.

2. Type 'GitHub Copilot: Collect Diagnostics' into the search bar.

3. Select the command from the dropdown list.

The editor will immediately open a new tab containing a formatted report. This report includes details about active proxy settings, extension versions, authentication tokens, and the status of connections to the backend endpoints.

If the diagnostic report indicates that the extension is failing to communicate, you must inspect the real-time output logs. By default, the log level is set to Info, which may hide the granular detail needed to identify certificate or network failures. To increase verbosity, run 'Developer: Set Log Level' from the Command Palette, select the 'Trace' option, and apply it to both the 'GitHub Copilot' and 'GitHub Copilot Chat' output channels.

Alternatively, you can configure these options directly in your global settings.json file to ensure trace logs are always collected:

{
  "github.copilot.chat.agentDebugLog.fileLogging.enabled": true,
  "github.copilot.chat.logLevel": "trace"
}

Once trace logging is enabled, open the Output panel in your editor (View > Output) and select 'GitHub Copilot' from the channel dropdown in the top-right corner. The log view will display every HTTP request, network connection lifecycle event, and JSON payload sent between the local editor and GitHub's servers. These logs are critical for identifying connection drops, token refresh failures, and request timeouts.

Developers can use the chat interface to ask for help. By typing /troubleshoot inside the chat panel, the local assistant will automatically analyze the active session's debug logs to suggest configuration fixes.

Developers working outside of Visual Studio Code can use IDE-specific diagnostics and terminal commands to check the status of GitHub Copilot. In JetBrains IDEs and Neovim environments, the extension runs as a background process that outputs logs directly to system files or custom console channels.

In JetBrains editors like IntelliJ IDEA, PyCharm, or WebStorm, the extension integrates its log messages into the standard application log. To locate these logs, open the Help menu and select 'Show Log in Finder' on macOS or 'Show Log in Explorer' on Windows. This action opens the directory containing idea.log. To make these logs useful for network debugging, you should enable trace logging for the extension. Navigate to Help > Diagnostic Tools > Debug Log Settings, and add this configuration line:

#com.github.copilot:trace

Once saved, the editor will record verbose connection logs in idea.log, highlighting any SSL handshake failures or proxy authentication drops.

For developers using Neovim, the official extension provides custom commands to verify authentication and connection health. To check if the local client is authenticated and connected, run this command in your editor:

:Copilot status

This command returns the active connection state, displaying whether the extension is online and ready. If the status command indicates an authentication failure, you can trigger the device authorization flow by running the login command:

:Copilot auth

To view details about your active user session and verified account settings, run:

:Copilot auth info

If you need to review the log file directly, you can open it in a new window using the editor command:

:Copilot log

For advanced troubleshooting when using Lua-based plugins such as copilot.lua, the extension operates like a local Language Server Protocol client. You can print the active client configuration to verify if Neovim is communicating with the background Node.js process by running:

:lua print(vim.inspect(vim.lsp.get_active_clients({ name = "copilot" })))

This output verifies that the background process is running, displays the port it is listening on, and lists the files it has indexed for context suggestions.

Proxy and SSL errors represent a major share of initial setup issues in enterprise environments. In restricted corporate networks, security systems frequently use SSL inspection, which decrypts and re-encrypts HTTPS traffic. Because these systems use custom certificate authorities, developer environments that lack these root certificates will reject the connection as an insecure intercept, resulting in connection errors.

When GitHub Copilot attempts to connect through an intercepting proxy, the trace logs will display errors such as unable to verify the first certificate, TLS/SSL handshake failure, or UNABLE_TO_GET_ISSUER_CERT_LOCALLY. To resolve these certificate errors, you must configure the local environment to trust the corporate certificate chain.

The first step is to locate your company's root certificate bundle, usually provided in a .pem or .crt file. You can configure Node.js based tools, including the GitHub Copilot extension, to respect this certificate bundle by defining an environment variable in your shell profile:

export NODE_EXTRA_CA_CERTS="/path/to/your/corporate-ca-certificates.pem"

This variable instructs the underlying Node runtime to append your custom certificates to the built-in trust store, allowing secure handshakes to succeed.

If the certificate issue persists in Visual Studio Code, you can modify how the editor handles certificate strictness. Open your settings.json file and add the proxy certificate setting:

{
  "http.proxyStrictSSL": false
}

Disabling strict SSL validation allows the connection to succeed, but it introduces security risks by permitting unverified certificates. This configuration should only be used as a temporary diagnostic step to isolate whether the root certificate configuration is the cause of the failure.

In JetBrains IDEs, you can manage custom certificates by opening your IDE settings, navigating to the Appearance & Behavior section, selecting System Settings, and choosing HTTP Proxy. From there, select 'Server Certificates' and check 'Accept non-trusted certificates automatically' to verify if the network intercept is blocking the connection, before importing the proper root certificates into the IDE's built-in trust store.

If you suspect proxy authentication is failing, ensure the environment variables are formatted correctly in your terminal shell:

export HTTPS_PROXY="http://username:password@proxy.example.com:8080"

Once defined, run curl -I https://github.com to confirm that standard web requests can pass through the proxy using these credentials.

Compile and analyze Copilot connection diagnostics with a shared team workspace

Centralize developer configurations, import root certificates, and semantic-search your log files using a persistent workspace with a built-in MCP server. Starts with a 14-day free trial.

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When developer environments experience recurring setup issues, team leaders must collect, analyze, and share diagnostic logs to coordinate fixes. Saving logs to individual text files or sharing them through chat applications leads to fragmented information and lacks structured indexing. To resolve this, teams can use shared workspaces to maintain a central directory of configurations, scripts, and logs.

Before setting up dedicated workflows, teams often consider basic alternatives. For example, local storage limits access to a single machine, preventing team collaboration. Basic object storage in public clouds keeps log files in the cloud but lacks semantic indexing, making searching through large text files difficult. Standard cloud folders do not expose clean API endpoints for coding agents, requiring developers to write custom download wrappers.

Fast.io offers an active workspace where developers and coding agents collaborate on the same files. Fast.io workspaces are org-owned, meaning all files, logs, and configurations reside under the organization's control. By enabling Intelligence Mode on a workspace, Fast.io automatically indexes uploaded files for semantic search. A developer can upload a diagnostic log file and immediately query it using natural language, retrieving specific error lines and citations without manual searching.

For unstructured log files, teams can use Metadata Views. This structured extraction layer turns documents into a live, queryable database. Users describe the fields they want extracted in natural language, and Fast.io designs a typed schema supporting Text, Integer, Decimal, Boolean, URL, JSON, and Date & Time. It matches files in the workspace and populates a spreadsheet, allowing teams to filter and sort logs by timestamp, error codes, and source machines.

Teams can connect their development assistants to these workspaces using the Fast.io MCP Server. The remote server is accessible via Streamable HTTP at the Fast.io MCP endpoint and legacy SSE at https://mcp.fast.io/sse. Developers can consult the Fast.io MCP documentation or the Fast.io LLM onboarding configuration page for setup details. In Visual Studio Code, you can register the Fast.io server in your configuration settings:

{
  "mcpServers": {
    "fastio-workspace": {
      "url": "https://mcp.fast.io/mcp"
    }
  }
}

With the Fast.io MCP server active, a developer's local coding assistant can write diagnostic reports directly into the workspace, search previous logs, and read Collaborative Notes containing network instructions. Fast.io preserves a complete per-file version history, ensuring that configuration updates do not overwrite team progress. If an agent writes a buggy settings file, developers can inspect the changes and restore a working version from the web interface. Once the connection setup is verified, the developer can transfer ownership of the troubleshooting workspace to human administrators, maintaining secure access control through organization permissions.

Every organization starts with a 14-day free trial, which requires a credit card. Subscription plans are detailed on the Fast.io pricing page and include the Starter plan at $29/mo, the Business plan at $99/mo, and the Growth plan at $299/mo. Creating an account is free; doing real work requires an organization on a paid subscription. This model ensures teams pay for organization-wide storage and seats with included credits covering AI operations, without relying on complex custom databases.