JSON MCP Server

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:

// 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

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

Shape Patterns

// 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

// 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)

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

Option 2: Global Install

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

Option 3: From Source

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

⚙️ MCP Integration

Claude Desktop

Add to your configuration file:

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

Claude Code

# 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

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

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

Deploy Server

HTTP connection URL

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Tools

Provides JSON schema generation and filtering tools for LLMs, helping with large JSON files by converting them to TypeScript definitions and extracting specific fields to reduce context size.

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JSON MCP Server

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

Tools

Related MCP Servers

Chroma MCP Server

JSON MCP Server

JSON Query MCP

Flexible Key-Value Extracting MCP Server

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