JSON MCP Filter

MCP server for JSON schema generation, smart filtering, and secure chunked data extraction.

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JSON MCP Filter is an MCP-compliant server offering robust JSON schema generation and field-level filtering tools for both local files and remote HTTP/HTTPS endpoints. Leveraging quicktype for precise TypeScript type creation, it supports advanced features such as smart shape-based filtering, auto-chunking of large datasets, and memory-safe processing. Designed for seamless integration with popular MCP clients, it excels at extracting and preparing relevant JSON data for large language model contexts.

Key Features

JSON to TypeScript interface conversion using quicktype

Shape-based smart field extraction

Support for processing both local files and remote HTTP/HTTPS API endpoints

Automatic chunking of large datasets (400KB per chunk)

Enforced 50MB processing limit for memory safety

Clear, actionable error messages and debug info

Integration with Claude Desktop and Claude Code via MCP

Dry run analysis for chunking recommendations

Metadata inclusion with chunked responses

Security guidelines for remote data fetching

Use Cases

Filtering and extracting specific fields from large JSON files

Pre-processing API responses for efficient LLM context ingestion

Converting incoming JSON to strict TypeScript types for application development

Handling massive datasets by splitting them into safe chunks for downstream use

Quickly analyzing JSON file structure and recommending optimal chunking strategies

Automating type-safe pipelines for data ingestion to AI models

Protecting memory usage during processing of huge JSON data

Fetching, sanitizing, and preparing remote JSON data for data science workflows

Debugging and troubleshooting complex datasets with detailed error reporting

Ensuring only relevant context is provided to LLMs during prompt engineering

README

JSON MCP Filter

A powerful Model Context Protocol (MCP) server that provides JSON schema generation and filtering tools for local files and remote HTTP/HTTPS endpoints. Built with quicktype for robust TypeScript type generation.

Perfect for: Filtering large JSON files and API responses to extract only relevant data for LLM context, while maintaining type safety.

✨ Key Features

🔄 Schema Generation - Convert JSON to TypeScript interfaces using quicktype
🎯 Smart Filtering - Extract specific fields with shape-based filtering
🌐 Remote Support - Works with HTTP/HTTPS URLs and API endpoints
📦 Auto Chunking - Handles large datasets with automatic 400KB chunking
🛡️ Size Protection - Built-in 50MB limit with memory safety
⚡ MCP Ready - Seamless integration with Claude Desktop and Claude Code
🚨 Smart Errors - Clear, actionable error messages with debugging info

🛠️ Available Tools

`json_schema`

Generates TypeScript interfaces from JSON data.

Parameters:

filePath: Local file path or HTTP/HTTPS URL

Example:

javascript

// Input JSON
{"name": "John", "age": 30, "city": "New York"}

// Generated TypeScript
export interface GeneratedType {
    name: string;
    age:  number;
    city: string;
}

`json_filter`

Extracts specific fields using shape-based filtering with automatic chunking for large datasets.

Parameters:

filePath: Local file path or HTTP/HTTPS URL
shape: Object defining which fields to extract
chunkIndex (optional): Chunk index for large datasets (0-based)

Auto-Chunking:

≤400KB: Returns all data
400KB: Auto-chunks with metadata

`json_dry_run`

Analyzes data size and provides chunking recommendations before filtering.

Parameters:

filePath: Local file path or HTTP/HTTPS URL
shape: Object defining what to analyze

Returns: Size breakdown and chunk recommendations

📋 Usage Examples

Basic Filtering

javascript

// Simple field extraction
json_filter({
  filePath: "https://api.example.com/users",
  shape: {"name": true, "email": true}
})

Shape Patterns

javascript

// Single field
{"name": true}

// Nested objects
{"user": {"name": true, "email": true}}

// Arrays (applies to each item)
{"users": {"name": true, "age": true}}

// Complex nested
{
  "results": {
    "profile": {"name": true, "location": {"city": true}}
  }
}

Large Dataset Workflow

javascript

// 1. Check size first
json_dry_run({filePath: "./large.json", shape: {"users": {"id": true}}})
// → "Recommended chunks: 6"

// 2. Get chunks
json_filter({filePath: "./large.json", shape: {"users": {"id": true}}})
// → Chunk 0 + metadata

json_filter({filePath: "./large.json", shape: {"users": {"id": true}}, chunkIndex: 1})
// → Chunk 1 + metadata

🔒 Security Notice

Remote Data Fetching: This tool fetches data from HTTP/HTTPS URLs. Users are responsible for:

✅ Safe Practices:

Verify URLs point to legitimate endpoints
Use trusted, public APIs only
Respect API rate limits and terms of service
Review data sources before processing

❌ Maintainers Not Responsible For:

External URL content
Privacy implications of remote requests
Third-party API abuse or violations

💡 Recommendation: Only use trusted, public data sources.

🚀 Quick Start

Option 1: NPX (Recommended)

bash

# No installation required
npx json-mcp-filter@latest

Option 2: Global Install

bash

npm install -g json-mcp-filter@latest
json-mcp-server

Option 3: From Source

bash

git clone <repository-url>
cd json-mcp-filter
npm install
npm run build

⚙️ MCP Integration

Claude Desktop

Add to your configuration file:

json

{
  "mcpServers": {
    "json-mcp-filter": {
      "command": "npx",
      "args": ["-y", "json-mcp-filter@latest"]
    }
  }
}

Claude Code

bash

# Add via CLI
claude mcp add json-mcp-filter npx -y json-mcp-filter@latest

Or add manually:

Name: json-mcp-filter
Command: npx
Args: ["-y", "json-mcp-filter@latest"]

🔧 Development

Commands

bash

npm run build      # Compile TypeScript
npm run start      # Run compiled server  
npm run inspect    # Debug with MCP inspector
npx tsc --noEmit   # Type check only

Testing

bash

npm run inspect    # Interactive testing interface

📁 Project Structure

src/
├── index.ts                    # Main server + tools
├── strategies/                 # Data ingestion strategies
│   ├── JsonIngestionStrategy.ts  # Abstract interface
│   ├── LocalFileStrategy.ts      # Local file access
│   └── HttpJsonStrategy.ts       # HTTP/HTTPS fetching
├── context/
│   └── JsonIngestionContext.ts   # Strategy management
└── types/
    └── JsonIngestion.ts          # Type definitions

🚨 Error Handling

Comprehensive Coverage

Local Files: Not found, permissions, invalid JSON
Remote URLs: Network failures, auth errors (401/403), server errors (500+)
Content Size: Auto-reject >50MB with clear messages
Format Detection: Smart detection of HTML/XML with guidance
Rate Limiting: 429 responses with retry instructions
Processing: Quicktype errors, shape filtering issues

All errors include actionable debugging information.

⚡ Performance

Processing Times

File Size	Processing Time
< 100 KB	< 10ms
1-10 MB	100ms - 1s
10-50 MB	1s - 5s
> 50 MB	Blocked

Size Protection

50MB maximum for all sources
Pre-download checking via Content-Length
Memory safety prevents OOM errors
Clear error messages with actual vs. limit sizes

Best Practices

Use json_dry_run first for large files
Filter with json_filter before schema generation
Focus shapes on essential fields only

🌐 Supported Sources

Public APIs - REST endpoints with JSON responses
Static Files - JSON files on web servers
Local Dev - http://localhost during development
Local Files - File system access

💡 Common Workflows

LLM Integration:

API returns large response
json_filter extracts relevant fields
Process clean data without noise
json_schema generates types for safety

Star History

Repository Owner

kehvinbehvin

User

Repository Details

Language JavaScript

Default Branch master

Size 95 KB

Contributors 3

License MIT License

MCP Verified Nov 12, 2025

Programming Languages

JavaScript

59.97%

TypeScript

40.03%

Topics

claude-mcp data data-extraction data-filtering json json-analysis json-filter json-mcp-server json-parser json-schema-inference json-to-typescript json-utilities large-files mcp mcp-server query type-generation

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JSON MCP Filter

Key Features

Use Cases

README

JSON MCP Filter

✨ Key Features

🛠️ Available Tools

json_schema

json_filter

json_dry_run

📋 Usage Examples

Basic Filtering

Shape Patterns

Large Dataset Workflow

🔒 Security Notice

🚀 Quick Start

Option 1: NPX (Recommended)

Option 2: Global Install

Option 3: From Source

⚙️ MCP Integration

Claude Desktop

Claude Code

🔧 Development

Commands

Testing

📁 Project Structure

🚨 Error Handling

Comprehensive Coverage

⚡ Performance

Processing Times

Size Protection

Best Practices

🌐 Supported Sources

💡 Common Workflows

Star History

Repository Owner

Repository Details

Programming Languages

Topics

Related MCPs

`json_schema`

`json_filter`

`json_dry_run`