troubleshooting

chromedevtools/chrome-devtools-mcp · updated May 26, 2026

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$npx skills add https://github.com/chromedevtools/chrome-devtools-mcp --skill troubleshooting
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summary

You are acting as a troubleshooting wizard to help the user configure and fix their Chrome DevTools MCP server setup. When this skill is triggered (e.g., because list_pages, new_page, or navigate_page failed, or the server wouldn't start), follow this step-by-step diagnostic process:

skill.md

Troubleshooting Wizard

You are acting as a troubleshooting wizard to help the user configure and fix their Chrome DevTools MCP server setup. When this skill is triggered (e.g., because list_pages, new_page, or navigate_page failed, or the server wouldn't start), follow this step-by-step diagnostic process:

Step 1: Find and Read Configuration

Your first action should be to locate and read the MCP configuration file. Search for the following files in the user's workspace: .mcp.json, gemini-extension.json, .claude/settings.json, .vscode/launch.json, or .gemini/settings.json.

If you find a configuration file, read and interpret it to identify potential issues such as:

  • Incorrect arguments or flags.
  • Missing environment variables.
  • Usage of --autoConnect in incompatible environments.

If you cannot find any of these files, only then should you ask the user to provide their configuration file content.

Step 2: Triage Common Connection Errors

Before reading documentation or suggesting configuration changes, check if the error message matches one of the following common patterns.

Error: Could not find DevToolsActivePort

This error is highly specific to the --autoConnect feature. It means the MCP server cannot find the file created by a running, debuggable Chrome instance. This is not a generic connection failure.

Your primary goal is to guide the user to ensure Chrome is running and properly configured. Do not immediately suggest switching to --browserUrl. Follow this exact sequence:

  1. Ask the user to confirm that the correct Chrome version (e.g., "Chrome Canary" if the error mentions it) is currently running.
  2. If the user confirms it is running, instruct them to enable remote debugging. Be very specific about the URL and the action: "Please open a new tab in Chrome, navigate to chrome://inspect/#remote-debugging, and make sure the 'Enable remote debugging' checkbox is checked."
  3. Once the user confirms both steps, your only next action should be to call the list_pages tool. This is the simplest and safest way to verify if the connection is now successful. Do not retry the original, more complex command yet.
  4. If list_pages succeeds, the problem is resolved. If it still fails with the same error, then you can proceed to the more advanced steps like suggesting --browserUrl or checking for sandboxing issues.

Symptom: Server starts but creates a new empty profile

If the server starts successfully but list_pages returns an empty list or creates a new profile instead of connecting to the existing Chrome instance, check for typos in the arguments.

  • Check for flag typos: For example, --autoBronnect instead of --autoConnect.
  • Verify the configuration: Ensure the arguments match the expected flags exactly.

Symptom: Missing Tools / Only 9 tools available

If the server starts successfully but only a limited subset of tools (like list_pages, get_console_message, lighthouse_audit, take_memory_snapshot) are available, this is likely because the MCP client is enforcing a read-only mode.

All tools in chrome-devtools-mcp are annotated with readOnlyHint: true (for safe, non-modifying tools) or readOnlyHint: false (for tools that modify browser state, like emulate, click, navigate_page). To access the full suite of tools, the user must disable read-only mode in their MCP client (e.g., by exiting "Plan Mode" in Gemini CLI or adjusting their client's tool safety settings).

Other Common Errors

Identify other error messages from the failed tool call or the MCP initialization logs:

  • Target closed
  • "Tool not found" (check if they are using --slim which only enables navigation and screenshot tools).
  • ProtocolError: Network.enable timed out or The socket connection was closed unexpectedly
  • Error [ERR_MODULE_NOT_FOUND]: Cannot find module
  • Any sandboxing or host validation errors.

Step 3: Read Known Issues

Read the contents of https://github.com/ChromeDevTools/chrome-devtools-mcp/blob/main/docs/troubleshooting.md to map the error to a known issue. Pay close attention to:

  • Sandboxing restrictions (macOS Seatbelt, Linux containers).
  • WSL requirements.
  • --autoConnect handshakes, timeouts, and requirements (requires running Chrome 144+).

Step 4: Formulate a Configuration

Based on the exact error and the user's environment (OS, MCP client), formulate the correct MCP configuration snippet. Check if they need to:

  • Pass --browser-url=http://127.0.0.1:9222 instead of --autoConnect (e.g. if they are in a sandboxed environment like Claude Desktop).
  • Enable remote debugging in Chrome (chrome://inspect/#remote-debugging) and accept the connection prompt. Ask the user to verify this is enabled if using --autoConnect.
  • Add --logFile <absolute_path_to_log_file> to capture debug logs for analysis.
  • Increase startup_timeout_ms (e.g. to 20000) if using Codex on Windows.

If you are unsure of the user's configuration, ask the user to provide their current MCP server JSON configuration.

Step 5: Run Diagnostic Commands

If the issue is still unclear, run diagnostic commands to test the server directly:

  • Run npx chrome-devtools-mcp@latest --help to verify the installation and Node.js environment.
  • If you need more information, run DEBUG=* npx chrome-devtools-mcp@latest --logFile=/tmp/cdm-test.log to capture verbose logs. Analyze the output for errors.

Step 6: Check GitHub for Existing Issues

If https://github.com/ChromeDevTools/chrome-devtools-mcp/blob/main/docs/troubleshooting.md does not cover the specific error, check if the gh (GitHub CLI) tool is available in the environment. If so, search the GitHub repository for similar issues: gh issue list --repo ChromeDevTools/chrome-devtools-mcp --search "<error snippet>" --state all

Alternatively, you can recommend that the user checks https://github.com/ChromeDevTools/chrome-devtools-mcp/issues and https://github.com/ChromeDevTools/chrome-devtools-mcp/discussions for help.

how to use troubleshooting

How to use troubleshooting on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add troubleshooting
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/chromedevtools/chrome-devtools-mcp --skill troubleshooting

The skills CLI fetches troubleshooting from GitHub repository chromedevtools/chrome-devtools-mcp and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/troubleshooting

Reload or restart Cursor to activate troubleshooting. Access the skill through slash commands (e.g., /troubleshooting) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.861 reviews
  • Soo Singh· Dec 28, 2024

    I recommend troubleshooting for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sofia Torres· Dec 28, 2024

    troubleshooting reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aisha Flores· Dec 24, 2024

    Solid pick for teams standardizing on skills: troubleshooting is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Dec 16, 2024

    troubleshooting fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ama Haddad· Dec 16, 2024

    Registry listing for troubleshooting matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Advait Malhotra· Dec 8, 2024

    Useful defaults in troubleshooting — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Advait Gonzalez· Dec 8, 2024

    I recommend troubleshooting for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Valentina Menon· Nov 27, 2024

    troubleshooting has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Advait Bhatia· Nov 27, 2024

    Solid pick for teams standardizing on skills: troubleshooting is focused, and the summary matches what you get after install.

  • Sofia Malhotra· Nov 23, 2024

    troubleshooting reduced setup friction for our internal harness; good balance of opinion and flexibility.

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