agentdiet-json-normalizer

x402

agentdiet-json-normalizer is a paid API for AI agents from agentdiet.dev, paid per call via x402 or MPP, $0.002/call, status unknown (last checked 2026-10-20).

Repairs truncated or malformed LLM JSON outputs (trailing commas, markdown fences, single quotes) so multi-agent pipelines never crash on bad JSON.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

Repairs truncated or malformed LLM JSON outputs (trailing commas, markdown fences, single quotes) so multi-agent pipelines never crash. (Live x402 v2, IETF MPP & MCP endpoint at https://agentdiet.dev/v1/json-normalizer)

Output

Returns a repaired, schema-valid JSON object with all syntax errors corrected: trailing commas removed, markdown fences stripped, single quotes converted to double quotes, and truncated structures closed. The response is immediately parseable JSON ready for downstream consumption in a multi-agent pipeline.

Example use cases

Fixing LLM pipeline crash on bad JSON

“My agent pipeline keeps crashing because the language model sometimes returns JSON with trailing commas or missing closing brackets — can you automatically repair whatever raw JSON string I pass in so the next step doesn't break?”

Stripping markdown fences from model output

“The model wrapped its JSON response in triple backtick markdown fences again — something like ```json {"result": true} ``` — can you strip those out and give me clean parseable JSON?”

Normalizing single-quoted JSON from agent

“One of my sub-agents is returning JSON with single quotes instead of double quotes, like {'key': 'value'} — can you normalize it to valid JSON so my downstream parser stops throwing errors?”

Technical details

Endpoint

GEThttps://agentdiet.dev/v1/json-normalizer?utm_source=zero.xyz

When to prefer

Choose this endpoint when your multi-agent pipeline receives LLM-generated JSON that fails standard JSON.parse() due to common LLM quirks: trailing commas, markdown code fences, single quotes, or mild truncation. It is deterministic (same input always yields same output), making it safe to use as a reliable normalization step. Prefer this over writing your own regex fixes when you want a hosted, pay-per-call microservice that handles the full range of common LLM JSON malformations without maintaining code.

Side effects

Input so severely malformed that deterministic repair is impossible — returns an error indicating unrecoverable JSON
Empty or null raw_json query parameter — returns validation error
Non-JSON content passed as input (e.g., plain text prose) — may return best-effort parse or error
Extremely long truncated JSON where structural intent cannot be inferred — may produce incorrect completion

Input

Schema · Request body

Field	Type	Description
raw_jsonrequired	string	Malformed, truncated, or markdown-wrapped JSON string to deterministically repair

Output

Schema · Response

{
  "type": "object"
}

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