by ackness
Fetch JSONPath retrieves and extracts data from HTTP APIs using JSONPath, supporting batch processing, custom headers, p
Fetches data from web APIs and extracts only the specific JSON fields you need using JSONPath patterns, reducing token usage by up to 99%. Supports batch processing and concurrent requests.
Fetch JSONPath is a community-built MCP server published by ackness that provides AI assistants with tools and capabilities via the Model Context Protocol. Fetch JSONPath retrieves and extracts data from HTTP APIs using JSONPath, supporting batch processing, custom headers, p It is categorized under search web. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.
You can install Fetch JSONPath in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Fetch JSONPath is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Share your MCP server with the developer community
We wired Fetch JSONPath into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
We wired Fetch JSONPath into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Fetch JSONPath benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Fetch JSONPath reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Fetch JSONPath is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Fetch JSONPath benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Useful MCP listing: Fetch JSONPath is the kind of server we cite when onboarding engineers to host + tool permissions.
We evaluated Fetch JSONPath against two servers with overlapping tools; this profile had the clearer scope statement.
Fetch JSONPath is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Fetch JSONPath has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
showing 1-10 of 70
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.
Reduce LLM Token Usage & Hallucination - Instead of fetching entire JSON responses and wasting tokens, extract only the data you need.
❌ Traditional fetch (wasteful):
// API returns 2000+ tokens
{
"data": [
{
"id": 1,
"name": "Alice",
"email": "[email protected]",
"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.
For most IDEs, use the uvx tool to run the server.
{
"mcpServers": {
"fetch-jsonpath-mcp": {
"command": "uvx",
"args": [
"fetch-jsonpath-mcp"
]
}
}
}
<details>
<summary><b>Install in Claude Code</b></summary>
claude mcp add fetch-jsonpath-mcp -- uvx fetch-jsonpath-mcp
</details>
<details>
<summary><b>Install in Cursor</b></summary>
{
"mcpServers": {
"fetch-jsonpath-mcp": {
"command": "uvx",
"args": ["fetch-jsonpath-mcp"]
}
}
}
</details>
<details>
<summary><b>Install in Windsurf</b></summary>
Add this to your Windsurf MCP config file. See Windsurf MCP docs for more info.
{
"mcpServers": {
"fetch-jsonpath-mcp": {
"command": "uvx",
"args": ["fetch-jsonpath-mcp"]
}
}
}
</details>
<details>
<summary><b>Install in VS Code</b></summary>
"mcp": {
"servers": {
"fetch-jsonpath-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["fetch-jsonpath-mcp"]
}
}
}
</details>
uv sync
# Install demo server dependencies
uv add fastapi uvicorn
# Start demo server on port 8080
uv run demo-server
uv run fetch-jsonpath-mcp
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"}
}
fetch-jsonExtract 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 headersfetch-textFetch 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 contentParameters:
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-jsonProcess 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 headersbatch-fetch-textFetch 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
..."}, {"url": "http://localhost:8080", "success": true, "content": "{"foo": [{"baz": 1, "qux": "a"}, {"baz": 2, "qux": "b"}]..."}]`
Supports:
This project uses jsonpath-ng for JSONPath implementation.
| Pattern | Result | Description |
|---|---|---|
foo[*].baz | [1, 2] | Get all baz values |
bar.items[*] | [10, 20, 30] | Get all items |
metadata.version | ["1.0.0"] | Get version |
For complete JSONPath syntax reference, see the jsonpath-ng documentation.
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:
Custom headers in JSONRPC_MCP_HEADERS will override defaults when there are conflicts.
# Run tests
pytest
# Check code quality
ruff check --fix
# Build and test locally
uv build
get-json → fetch-json, get-text → fetch-textmarkdownifyInteract with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.