# MCP Response Normalizer (`junipr/mcp-response-normalizer`) Actor

Normalize MCP tool responses into consistent structured records by parsing content blocks, JSON payloads, text responses, attachments, errors, metadata, and schema-mapped output fields.

- **URL**: https://apify.com/junipr/mcp-response-normalizer.md
- **Developed by:** [junipr](https://apify.com/junipr) (community)
- **Categories:** SEO tools, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $6.50 / 1,000 schema validateds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## MCP Response Normalizer

### Store Positioning

**Store title:** MCP Response Normalizer

**Short description:** Normalize MCP tool responses into consistent structured records by parsing content blocks, JSON payloads, text responses, attachments, errors, metadata, and schema-mapped output fields.

**SEO title:** MCP Response Normalizer — API, schema, and developer QA

**SEO description:** Normalize MCP tool responses into consistent structured records by parsing content blocks, JSON payloads, text responses, attachments, errors, metadata, and schema-mapped output fields. Use it to catch contract drift, schema mistakes, unsafe endpoint assumptions, and developer-tool quality issues before release.

**Categories:** SEO\_TOOLS, DEVELOPER\_TOOLS

**Keywords:** mcp, response, normalizer, structured data, schema, data qa, api/developer qa

### Pay-Per-Event Pricing

This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model.

- Tier: A1 — API/developer QA
- Primary event: `schema-validated` at $0.00650 base
- Default max charge: $10.00
- Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount

Event set:

- `actor-start`: base $0.00500, GOLD $0.00400. MCP Response Normalizer: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
- `schema-validated`: base $0.00650, GOLD $0.00520. MCP Response Normalizer: charged when schema validated is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
- `contract-rule-checked`: base $0.00390, GOLD $0.00312. MCP Response Normalizer: charged when contract rule checked is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
- `report-generated`: base $0.05000, GOLD $0.04000. MCP Response Normalizer: charged when report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended.

### Public Task Concepts

- Extract MCP Response rows from supplied public inputs
- Inventory MCP Response fields across a capped sample
- Normalize MCP Response evidence for delivery
- Flag missing MCP Response data before delivery
- Export MCP Response records with source URLs

Normalize heterogeneous MCP tool responses into consistent dataset rows. The actor accepts JSON responses, response logs, text responses, expected schemas, and mapping rules, then extracts content blocks, parsed JSON, normalized records, schema validity, error blocks, resource URIs, and attachment metadata.

### Inputs

Provide `responseJsonInputs`, `responseLogInputs`, `textResponses`, `expectedSchemas`, `schemaMappings`, `normalizationMode`, `extractJsonFromText`, `includeRawResponse`, `includeErrorBlocks`, `maxResponses`, `maxResponseBytes`, and `timeoutMs`. The defaults are capped so accidental huge logs do not create expensive runs.

### Output

Rows include `sourceId`, `toolName`, `responseIndex`, `responseType`, `contentType`, `contentBlockType`, `parsedJson`, `normalizedRecord`, `schemaValid`, `fieldPath`, `errorCode`, `errorMessage`, `resourceUri`, `attachmentName`, `normalizationWarning`, and `confidence`. KVS reports summarize normalized records, schema failures, and parse warnings.

### Billing safety

The actor charges `actor-start` before analysis, charges the primary PPE event before each dataset row, and charges the report event before writing report artifacts. `maxChargeUsd` stops work or output gracefully before the configured cap is exceeded.

# Actor input Schema

## `responseJsonInputs` (type: `array`):

Supplied input records for MCP Response Normalizer to process without additional discovery.

## `responseLogInputs` (type: `array`):

Supplied input records for MCP Response Normalizer to process without additional discovery.

## `textResponses` (type: `array`):

Supplied responses for MCP Response Normalizer to validate without making live requests.

## `expectedSchemas` (type: `array`):

Expected schemas used for comparison and validation.

## `schemaMappings` (type: `array`):

Schema Mappings controls MCP Response Normalizer processing for the supplied inputs; keep values conservative for first runs.

## `normalizationMode` (type: `string`):

Normalization Mode controlling how MCP Response Normalizer processes the supplied inputs.

## `extractJsonFromText` (type: `boolean`):

Extract JSON from text when enough evidence is available.

## `includeRawResponse` (type: `boolean`):

Include raw response in output rows or reports when available.

## `includeErrorBlocks` (type: `boolean`):

Include error blocks in output rows or reports when available.

## `maxResponses` (type: `number`):

Maximum responses to process in one run; keep defaults low for safe first runs.

## `maxResponseBytes` (type: `number`):

Maximum response bytes to process in one run; keep defaults low for safe first runs.

## `timeoutMs` (type: `number`):

Maximum time in milliseconds allowed for the MCP Response Normalizer operation before it is treated as timed out.

## `maxChargeUsd` (type: `number`):

Maximum estimated PPE charge allowed for the run before the actor stops gracefully.

## Actor input object example

```json
{
  "responseJsonInputs": [
    {
      "sourceId": "mcp-tools-call-weather",
      "toolName": "get_weather",
      "content": [
        {
          "type": "text",
          "text": "{\"temperature\":22.5,\"conditions\":\"Partly cloudy\"}"
        }
      ]
    }
  ],
  "responseLogInputs": [],
  "textResponses": [],
  "expectedSchemas": [
    {
      "type": "object",
      "required": [
        "temperature",
        "conditions"
      ],
      "properties": {
        "temperature": {
          "type": "number",
          "title": "Temperature",
          "description": "Temperature input value."
        },
        "conditions": {
          "type": "string",
          "title": "Conditions",
          "description": "Conditions input value."
        }
      }
    }
  ],
  "schemaMappings": [],
  "normalizationMode": "record",
  "extractJsonFromText": true,
  "includeRawResponse": false,
  "includeErrorBlocks": true,
  "maxResponses": 5,
  "maxResponseBytes": 10000,
  "timeoutMs": 5000,
  "maxChargeUsd": 1
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("junipr/mcp-response-normalizer").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("junipr/mcp-response-normalizer").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 '{}' |
apify call junipr/mcp-response-normalizer --silent --output-dataset

```

## MCP server setup

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

```

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/EDbKnSSiwZgn1bsAp/builds/ENiRNbtA3h0SY53Ph/openapi.json