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Editorial snapshot from September 2026. Prices, models and interface labels may change; this is a practical guide, not a live product feed.
A practical triage checklist for installation, login, models, extensions and MCP.
Installation or launch failure
Use the official download center and match the operating system and architecture. Note the error message before retrying. On Linux, select the package format appropriate to your distribution. On macOS, do not assume an old Intel installer is still the supported build.
Login or network errors
Check whether the account can sign in on the official website. Record the time and error code, and check whether a proxy, VPN or organization policy affects the client. Avoid repeated reinstalls until you have separated an account problem from a local client problem.
Model unavailable or token limit reached
Check the current plan, remaining usage and model picker. Test a small new conversation. If the account has exhausted its allowance, reinstalling the editor will not restore it. Review the price and usage controls before enabling additional spending.
MCP server will not start
Validate JSON, confirm the executable is available to the IDE, and inspect the server log. A shell with a working npx command may have a different PATH from a desktop application. Use the MCP guide for a step-by-step checklist.
Extensions or indexing problems
Try a small project and temporarily disable a suspected extension to isolate the cause. Check workspace size and exclude generated output where the client supports it. Back up settings before resetting anything; keep a short reproduction for official support.
What to include in a support report
Include client version, operating system, architecture, region, plan, the smallest reproduction and a redacted error log. Never attach access tokens, environment files or private source code unless you have reviewed what is being shared.
A complete first task: change, verify and review
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Choose a small repository that already builds. Save a clean Git checkpoint and write down the command that currently passes. This gives you a baseline for distinguishing an existing problem from a generated regression.
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Describe one observable result: for example, add a required field to an existing form and show an error without submitting invalid data. Include the relevant files, existing validation helper and the behavior that must stay unchanged.
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Ask for a short plan before editing. Check that it names the affected components, data flow and verification command. Resolve missing context before allowing a broad refactor.
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Review the diff in small batches. Check dependencies, generated files, environment variables and error handling as well as the visible result. Run the project checks and exercise both the successful and failing paths.
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Inspect the usage record after the task. Record the accepted outcome, review time and usage consumed. Repeat on a second representative task before choosing a paid plan or moving a team workflow.
A task brief you can adapt
Goal: describe the user-visible change.
Context: list the relevant files and existing implementation.
Constraints: keep the public API and use the existing dependencies.
Verification: run the repository's documented checks and test the failure path.
Completion: summarize changed files, checks performed and remaining limitations.When the result is not usable
A successful request does not prove the code works. If the agent edits the wrong files, reduce the scope and supply the entry point explicitly. If a command fails, reproduce it in the same terminal environment before changing the prompt. If an MCP connection fails, separate server startup, credentials and client configuration. If usage is exhausted, check the account balance and selected model before repeating the same request. Keep a failed patch small enough to revert without losing unrelated work.
Common questions before you switch
Does a paid subscription mean unlimited agent work?
No. Subscription price, included usage, model access and additional usage are different things. A plan with unlimited autocomplete does not imply unlimited model requests or cloud tasks.
Should I connect every MCP server at once?
Start with the one integration needed by your current task. Confirm that it starts, exposes the expected tools and receives only the intended project context before adding another.
How should I compare two AI editors?
Use the same repository, task and acceptance checks. Compare correct changes, review effort, setup friction and recorded usage. A long feature list does not establish which editor produces better code for your project.
Related TRAE guides
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