-
security-
license-
qualityExtract structured data from any website with a simple SDK call. No scraping code, no headless browsers - just prompt and get JSON.
Last updated -
49
The Fetch JSONPath MCP server is a Model Context Protocol server that provides efficient web scraping and data extraction tools designed to reduce LLM token usage and hallucination by extracting only necessary information.
Extract Specific JSON Data: Fetch JSON content from URLs and precisely extract data using basic and extended JSONPath patterns, supporting filtering, arithmetic operations, length checks, and text transformations
Fetch Web Content: Retrieve web content in multiple formats including intelligent Markdown (default), clean plain text, or raw HTML
Batch Processing: Concurrently process multiple URLs for both JSON extraction and text fetching, optimizing performance by fetching unique URLs only once
Multi-Method HTTP Support: Execute requests using GET, POST, PUT, DELETE, PATCH, HEAD, and OPTIONS methods with custom request bodies and headers
Smart Browser Headers: Automatically include browser-like headers merged with custom headers to prevent blocking and ensure reliable web access
Configurable Behavior: Customize server operations through environment variables for timeout, SSL verification, redirect following, and HTTP proxy settings
Efficient Token Usage: Extract only required data to minimize token consumption, reduce costs, and improve model accuracy
Fetch JSONPath MCP
A Model Context Protocol (MCP) server that provides tools for fetching JSON data and web content from URLs. Features intelligent content extraction, multiple HTTP methods, and browser-like headers for reliable web scraping.
🎯 Why Use This?
Reduce LLM Token Usage & Hallucination - Instead of fetching entire JSON responses and wasting tokens, extract only the data you need.
Traditional Fetch vs JSONPath Extract
❌ Traditional fetch (wasteful):
// API returns 2000+ tokens
{
"data": [
{
"id": 1,
"name": "Alice",
"email": "alice@example.com",
"avatar": "https://...",
"profile": {
"bio": "Long bio text...",
"settings": {...},
"preferences": {...},
"metadata": {...}
},
"posts": [...],
"followers": [...],
"created_at": "2023-01-01",
"updated_at": "2024-01-01"
},
// ... 50 more users
],
"pagination": {...},
"meta": {...}
}
✅ JSONPath extract (efficient):
// Only 10 tokens - exactly what you need!
["Alice", "Bob", "Charlie"]
Using pattern: data[*].name saves 99% tokens and eliminates model hallucination from irrelevant data.
Installation
For most IDEs, use the uvx tool to run the server.
{
"mcpServers": {
"fetch-jsonpath-mcp": {
"command": "uvx",
"args": [
"fetch-jsonpath-mcp"
]
}
}
}
claude mcp add fetch-jsonpath-mcp -- uvx fetch-jsonpath-mcp
{
"mcpServers": {
"fetch-jsonpath-mcp": {
"command": "uvx",
"args": ["fetch-jsonpath-mcp"]
}
}
}
Add this to your Windsurf MCP config file. See Windsurf MCP docs for more info.
Windsurf Local Server Connection
{
"mcpServers": {
"fetch-jsonpath-mcp": {
"command": "uvx",
"args": ["fetch-jsonpath-mcp"]
}
}
}
"mcp": {
"servers": {
"fetch-jsonpath-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["fetch-jsonpath-mcp"]
}
}
}
Development Setup
1. Install Dependencies
uv sync
2. Start Demo Server (Optional)
# Install demo server dependencies
uv add fastapi uvicorn
# Start demo server on port 8080
uv run demo-server
3. Run MCP Server
uv run fetch-jsonpath-mcp
Demo Server Data
The demo server at http://localhost:8080 returns:
{
"foo": [{"baz": 1, "qux": "a"}, {"baz": 2, "qux": "b"}],
"bar": {
"items": [10, 20, 30],
"config": {"enabled": true, "name": "example"}
},
"metadata": {"version": "1.0.0"}
}
Available Tools
fetch-json
Extract JSON data using JSONPath patterns with support for all HTTP methods.
{
"name": "fetch-json",
"arguments": {
"url": "http://localhost:8080",
"pattern": "foo[*].baz",
"method": "GET"
}
}
Returns: [1, 2]
Parameters:
url(required): Target URLpattern(optional): JSONPath pattern for data extractionmethod(optional): HTTP method (GET, POST, PUT, DELETE, etc.) - Default: "GET"data(optional): Request body for POST/PUT requestsheaders(optional): Additional HTTP headers
fetch-text
Fetch web content with intelligent text extraction. Defaults to Markdown format for better readability.
{
"name": "fetch-text",
"arguments": {
"url": "http://localhost:8080",
"output_format": "clean_text"
}
}
Returns: Clean text representation of the JSON data
Output Formats:
"markdown"(default): Converts HTML to clean Markdown format"clean_text": Pure text with HTML tags removed"raw_html": Original HTML content
Parameters:
url(required): Target URLmethod(optional): HTTP method - Default: "GET"data(optional): Request body for POST/PUT requestsheaders(optional): Additional HTTP headersoutput_format(optional): Output format - Default: "markdown"
batch-fetch-json
Process multiple URLs with different JSONPath patterns concurrently.
{
"name": "batch-fetch-json",
"arguments": {
"requests": [
{"url": "http://localhost:8080", "pattern": "foo[*].baz"},
{"url": "http://localhost:8080", "pattern": "bar.items[*]"}
]
}
}
Returns: [{"url": "http://localhost:8080", "pattern": "foo[*].baz", "success": true, "content": [1, 2]}, {"url": "http://localhost:8080", "pattern": "bar.items[*]", "success": true, "content": [10, 20, 30]}]
Request Object Parameters:
url(required): Target URLpattern(optional): JSONPath patternmethod(optional): HTTP method - Default: "GET"data(optional): Request bodyheaders(optional): Additional HTTP headers
batch-fetch-text
Fetch content from multiple URLs with intelligent text extraction.
{
"name": "batch-fetch-text",
"arguments": {
"requests": [
"http://localhost:8080",
{"url": "http://localhost:8080", "output_format": "raw_html"}
],
"output_format": "markdown"
}
}
Returns: [{"url": "http://localhost:8080", "success": true, "content": "# Demo Server Data\n\n..."}, {"url": "http://localhost:8080", "success": true, "content": "{\"foo\": [{\"baz\": 1, \"qux\": \"a\"}, {\"baz\": 2, \"qux\": \"b\"}]..."}]
Supports:
Simple URL strings
Full request objects with custom methods and headers
Mixed input types in the same batch
JSONPath Examples
This project uses jsonpath-ng for JSONPath implementation.
Pattern | Result | Description |
|
| Get all baz values |
|
| Get all items |
|
| Get version |
For complete JSONPath syntax reference, see the jsonpath-ng documentation.
🚀 Performance Benefits
Token Efficiency: Extract only needed data, not entire JSON responses
Faster Processing: Smaller payloads = faster LLM responses
Reduced Hallucination: Less irrelevant data = more accurate outputs
Cost Savings: Fewer tokens = lower API costs
Better Focus: Clean data helps models stay on task
Smart Headers: Default browser headers prevent blocking and improve access
Markdown Conversion: Clean, readable format that preserves structure
Configuration
Set environment variables to customize behavior:
# Request timeout in seconds (default: 10.0)
export JSONRPC_MCP_TIMEOUT=30
# SSL verification (default: true)
export JSONRPC_MCP_VERIFY=false
# Follow redirects (default: true)
export JSONRPC_MCP_FOLLOW_REDIRECTS=true
# Custom headers (will be merged with default browser headers)
export JSONRPC_MCP_HEADERS='{"Authorization": "Bearer token"}'
# HTTP proxy configuration
export JSONRPC_MCP_PROXY="http://proxy.example.com:8080"
Default Browser Headers: The server automatically includes realistic browser headers to prevent blocking:
User-Agent: Chrome browser simulation
Accept: Standard browser content types
Accept-Language, Accept-Encoding: Browser defaults
Security headers: Sec-Fetch-* headers for modern browsers
Custom headers in JSONRPC_MCP_HEADERS will override defaults when there are conflicts.
Development
# Run tests
pytest
# Check code quality
ruff check --fix
# Build and test locally
uv build
What's New in v1.1.0
✨ Multi-Method HTTP Support: GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS
🔄 Tool Renaming:
get-json→fetch-json,get-text→fetch-text📄 Markdown Conversion: Default HTML to Markdown conversion with
markdownify🌐 Smart Browser Headers: Automatic browser simulation headers
🎛️ Format Control: Three output formats for text content (markdown, clean_text, raw_html)
🚀 Enhanced Batch Processing: Support for different methods in batch operations
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