# JSON Fixer (`flyerlin/json-fixer`) Actor

Repairs malformed JSON such as LLM output: strips Markdown fences, fixes curly quotes and trailing commas, and optionally validates the result against a JSON Schema.

- **URL**: https://apify.com/flyerlin/json-fixer.md
- **Developed by:** [林 吴](https://apify.com/flyerlin) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 json cleaneds

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## JSON Fixer

Repair malformed JSON from LLMs, logs, and hand-edited config files. Paste raw text and get valid, parsed JSON back.

### What it does

- Strips Markdown code fences (for example, json-fenced blocks) and surrounding prose
- Replaces curly quotes (“ ” ‘ ’) with straight quotes
- Removes trailing commas before `}` and `]`
- Removes UTF-8 BOM and whitespace noise
- Supports both JSON objects and top-level arrays
- Optionally validates the result against a JSON Schema and reports field-level errors

### Input

| Field | Type | Required | Description |
| --- | --- | --- | --- |
| `raw_text` | string | Yes | Raw text that may contain Markdown, curly quotes, trailing commas, or missing brackets |
| `expected_schema` | string | No | JSON Schema (as a JSON string) used to validate the cleaned result |

Example input:

```json
{
  "raw_text": "Here is the result:\n{\"name\": \"Lin\", \"tags\": [\"json\", \"cleanup\",], \"quote\": “hello”}",
  "expected_schema": "{\"type\":\"object\",\"required\":[\"name\"]}"
}
```

### Output

One item is pushed to the default dataset:

```json
{
  "success": true,
  "cleaned_json": {
    "name": "Lin",
    "tags": ["json", "cleanup"],
    "quote": "hello"
  },
  "errors": []
}
```

If parsing or schema validation fails, `success` is `false`, `cleaned_json` is `{}`, and `errors` contains the parser or validation messages.

### Pricing

Pay per event. The **$0.01** charge applies only when the JSON is successfully repaired and parsed. Failed attempts are not charged the repair fee, but standard start and dataset events still apply.

### Use cases

- Cleaning structured output from LLM APIs before downstream processing
- Fixing JSON copied from chat, docs, or logs
- Validating scraped data against an expected schema
- Preparing malformed config snippets for automation pipelines

### Notes

This Actor performs deterministic string repair; it does not call any external AI model, so results are fast and reproducible.

# Actor input Schema

## `raw_text` (type: `string`):

需要清洗的原始文本，可能是带 Markdown 围栏的 JSON，也可能包含中文引号或尾逗号。

## `expected_schema` (type: `string`):

预期的 JSON Schema（JSON 字符串格式），提供后会对清洗结果做字段级校验。

## Actor input object example

```json
{
  "raw_text": "Here is the result:\n{\"name\": \"Lin\", \"tags\": [\"json\", \"cleanup\",], \"quote\": “hello”}"
}
```

# Actor output Schema

## `results` (type: `string`):

Cleaned JSON result with a success flag and any schema validation errors.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "raw_text": `Here is the result:
{"name": "Lin", "tags": ["json", "cleanup",], "quote": “hello”}`
};

// Run the Actor and wait for it to finish
const run = await client.actor("flyerlin/json-fixer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "raw_text": """Here is the result:
{\"name\": \"Lin\", \"tags\": [\"json\", \"cleanup\",], \"quote\": “hello”}""" }

# Run the Actor and wait for it to finish
run = client.actor("flyerlin/json-fixer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "raw_text": "Here is the result:\\n{\\"name\\": \\"Lin\\", \\"tags\\": [\\"json\\", \\"cleanup\\",], \\"quote\\": “hello”}"
}' |
apify call flyerlin/json-fixer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,flyerlin/json-fixer"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/kDAVdFUTckNhxxX2y/builds/wClmYPua6DRlmn960/openapi.json