Automatically fix missing quotes, trailing commas, bracket mismatches, single quotes, and escape issues. Supports local repair first, with AI-assisted deep repair when needed.
When you enter invalid JSON, the system tries these methods in order:
Start repairing JSON
Enter broken JSON or import a file to begin recovery.
Repair JSON works best between validation and formatting. Start with the raw broken payload, let the tool try deterministic local repair first, use AI-assisted repair only if needed, then move the recovered JSON into validation, formatting, or export.
Recover broken text into usable JSON
A lot of broken JSON is not just ugly - it is completely unusable. The repair step matters because it gets that payload back into a valid JSON shape so validation, formatting, comparison, and export are possible again.
If the JSON is too broken to parse at all, starting with Repair JSON is often faster than starting with manual validation.
Repair JSON is usually used for messy real-world payloads, not classroom examples. These examples match common issues in legacy systems, config cleanup, and corrupted logs.
Useful for old systems, script-generated payloads, or manually assembled responses that almost look like JSON but are not actually valid.
This category is usually fixed by local repair alone, without needing AI.
Teams often write JavaScript object style config and only realize later that strict JSON does not allow comments or trailing commas.
Repair JSON is ideal for pulling almost-JSON config back into a strict JSON form.
When a payload includes truncation, escape damage, and multiple bracket errors at once, deterministic local rules may not be enough. That is where AI repair becomes useful.
After this kind of repair, validate the result again before trusting it in downstream workflows.
Tutorial Step
Step 1 - Import the raw broken JSON without over-editing it first
The repair tool needs the original context more than a half-cleaned version. Logs, old API responses, and broken config files are often easier to repair when you keep the raw text intact instead of manually deleting large sections first.
Tutorial Step
Step 2 - Let local repair run first, then decide whether AI is needed
Not every repair uses AI. Most broken JSON is fixed by deterministic local rules, so the real goal here is to understand the repair order instead of assuming every issue needs an AI rewrite.
Tutorial Step
Step 3 - Verify that the result is both parseable and still correct
A successful repair is not only about making the JSON parse again. You also need to confirm that the result still matches the intended business structure, especially for nested objects, arrays, and partially corrupted logs.
Tutorial Step
Step 4 - Pass the repaired JSON into validation, formatting, and the rest of the workflow
Repair is the recovery step, not the final destination. Once the JSON is usable again, you should immediately move it into the right next tool depending on whether you need validation, readability, schema generation, or field-level review.
A more reliable repair workflow
Paste the raw broken JSON into Repair JSON before doing broad manual cleanup.
Let local repair run first and use that result when it is enough, rather than forcing every case through AI.
If the structure is still too broken, split the payload or let AI repair handle the more complex reconstruction.
Validate the repaired output next, then move it to the formatter, table editor, or schema tools depending on your goal.
If the result matters for team review or rollback, download the repaired version instead of only copying it to the clipboard.
Repair JSON is most useful not because it saves one comma fix, but because it recovers data that would otherwise be blocked from the rest of your JSON workflow.
Practical repair tips
Validate repaired JSON strictly and pinpoint any remaining problems.
Pretty-print or minify repaired JSON with consistent indentation options.
Generate JSON Schema from the repaired payload for stronger validation later.
Convert the repaired JSON into TypeScript interfaces or types.
Inspect and edit repaired JSON visually in a spreadsheet-like table view.
The page repairs JSON in layers. It starts with local methods such as the JSONRepair library and basic rule-based fixes, then uses AI repair only when the structure is too damaged or ambiguous for deterministic local repair alone.
Common repairable issues include missing quotes around keys, trailing commas, unclosed arrays or objects, single quotes used in place of double quotes, missing commas, broken escapes, and lightly corrupted structure.
AI repair is used only when local repair is not enough to recover the intended structure. Typical cases include nested log payloads, heavily broken legacy config, truncated objects, or JSON mixed into semi-structured text.
Most common repairs happen fully in the browser and never leave your device. Only when complex AI repair is required does the JSON get sent to an AI provider for processing, and we do not store it or use it for training.
Yes. For stability, AI repair supports inputs of roughly ~18000 characters per request. Larger payloads usually work better when split into smaller chunks or cleaned first with local repair.
No. You do not need to supply any API key to use the built-in local repair flow, and AI repair is already wired in when it is needed.
Yes. Repair is designed to recover broken JSON into something parseable again. Validation is still the best final check to confirm that the structure, syntax, and warnings all look correct.
If large sections of the payload are missing, truncated, or business meaning depends on context only you know, automatic repair can only recover syntax, not your original intent. In that case, combine validator diagnostics with manual fixes.
