by yshalsager
4get is a privacy-focused private search engine that aggregates web, image, and news results while protecting your data
Provides privacy-focused web searches through the 4get meta search engine, which aggregates results from multiple sources without tracking users.
4get is a community-built MCP server published by yshalsager that provides AI assistants with tools and capabilities via the Model Context Protocol. 4get is a privacy-focused private search engine that aggregates web, image, and news results while protecting your data It is categorized under search web.
You can install 4get 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.
GPL-3.0
4get is released under the GPL-3.0 license.
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
4get is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
4get has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired 4get into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Useful MCP listing: 4get is the kind of server we cite when onboarding engineers to host + tool permissions.
4get is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
4get reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
According to our notes, 4get benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
4get is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
4get is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
4get is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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A MCP server that provides seamless access to the 4get Meta Search engine API for LLM clients via FastMCP.
engine parameter without memorizing query strings# Install dependencies
uv sync
# Run the server
uv run -m mcp_4get
# Or use mise
mise run
The server is highly configurable via environment variables. All settings have sensible defaults for the public https://4get.ca instance.
| Variable | Description | Default |
|---|---|---|
FOURGET_BASE_URL | Base URL for the 4get instance | https://4get.ca |
FOURGET_PASS | Optional pass token for rate-limited instances | unset |
FOURGET_USER_AGENT | Override User-Agent header | mcp-4get/<version> |
FOURGET_TIMEOUT | Request timeout in seconds | 20.0 |
| Variable | Description | Default |
|---|---|---|
FOURGET_CACHE_TTL | Cache lifetime in seconds | 600.0 |
FOURGET_CACHE_MAXSIZE | Maximum cached responses | 128 |
FOURGET_CONNECTION_POOL_MAXSIZE | Max concurrent connections | 10 |
FOURGET_CONNECTION_POOL_MAX_KEEPALIVE | Max persistent connections | 5 |
| Variable | Description | Default |
|---|---|---|
FOURGET_MAX_RETRIES | Maximum retry attempts | 3 |
FOURGET_RETRY_BASE_DELAY | Base retry delay in seconds | 1.0 |
FOURGET_RETRY_MAX_DELAY | Maximum retry delay in seconds | 60.0 |
uv run -m mcp_4get
# With custom configuration
export FOURGET_BASE_URL="https://my-4get-instance.com"
export FOURGET_PASS="my-secret-token"
export FOURGET_CACHE_TTL="300"
export FOURGET_MAX_RETRIES="5"
uv run -m mcp_4get
You can integrate the 4get MCP server with popular IDEs and AI assistants. Here are configuration examples:
Add this to your Cursor MCP configuration (~/.cursor/mcp.json):
{
"mcpServers": {
"4get": {
"command": "uvx",
"args": [
"mcp_4get@latest"
],
"env": {
"FOURGET_BASE_URL": "https://4get.ca"
}
}
}
}
Add this to your Codex MCP configuration (~/.codex/config.toml):
[mcp_servers.4get]
command = "uvx"
args = ["mcp_4get@latest"]
env = { FOURGET_BASE_URL = "https://4get.ca" }
Note: Replace /path/to/your/mcp-4get with the actual path to your project directory.
The server exposes three powerful search tools with comprehensive response formatting:
fourget_web_searchfourget_web_search(
query: str,
page_token: str = None, # Use 'npt' from previous response
extended_search: bool = False, # Enable extended search mode
engine: str = None, # Pick a scraper from the supported engine list
extra_params: dict = None # Language, region, etc.
)
Response includes: web[], answer[], spelling, related[], npt
fourget_image_searchfourget_image_search(
query: str,
page_token: str = None, # Use 'npt' from previous response
engine: str = None, # Pick a scraper from the supported engine list
extra_params: dict = None # Size, color, type filters
)
Response includes: image[], npt
fourget_news_searchfourget_news_search(
query: str,
page_token: str = None, # Use 'npt' from previous response
engine: str = None, # Pick a scraper from the supported engine list
extra_params: dict = None # Date range, source filters
)
Response includes: news[], npt
All MCP tools accept an optional engine argument that maps directly to the 4get scraper query parameter. This shorthand overrides any scraper value you may include in extra_params.
| Value | Engine |
|---|---|
ddg | DuckDuckGo |
brave | Brave |
mullvad_brave | Mullvad (Brave) |
yandex | Yandex |
google | |
google_cse | Google CSE |
mullvad_google | Mullvad (Google) |
startpage | Startpage |
qwant | Qwant |
ghostery | Ghostery |
yep | Yep |
greppr | Greppr |
crowdview | Crowdview |
mwmbl | Mwmbl |
mojeek | Mojeek |
baidu | Baidu |
coccoc | Coc Coc |
solofield | Solofield |
marginalia | Marginalia |
wiby | wiby |
curlie | Curlie |
If you need to pass additional 4get query parameters (such as country or language), continue to supply them through extra_params.
All tools support pagination via the npt (next page token):
# Get first page
result = await client.web_search("python programming")
# Get next page if available
if result.get('npt'):
next_page = await client.web_search("ignored", page_token=result['npt'])
You can reuse the bundled async client outside MCP for direct API access:
import asyncio
from mcp_4get.client import FourGetClient
from mcp_4get.config import Config
async def main() -> None:
client = FourGetClient(Config.from_env())
data = await client.web_search(
"model context protocol",
options={"scraper": "mullvad_brave"},
)
for result in data.get("web", []):
print(result["title"], "->", result["url"])
asyncio.run(main())
This allows you to integrate 4get search capabilities directly into your Python applications without going through the MCP protocol.
FourGetAuthError: Rate limited or invalid authenticationFourGetAPIError: API returned non-success statusFourGetTransportError: Network or HTTP protocol errorsFourGetError: Generic client errorsAll settings are validated on startup with clear error messages for misconfigurations.
Based on the real 4get API, responses include rich metadata:
{
"status": "ok",
"web": [
{
"title": "Example Result",
"description": "Result description...",
"url": "https://example.com",
"date": 1640995200,
"type": "web"
}
],
"answer": [
{
"title": "Featured Answer",
"description": [{"type": "text", "value": "Answer content..."}],
"url": "https://source.com",
"table": {"Key": "Value"}
}
],
"spelling": {
"type": "no_correction",
"correction": null
},
"related": ["related search", "terms"],
"npt": "pagination_token_here"
}
This project uses several tools to streamline the development process:
mise is used for managing project-level dependencies and environment variables. mise helps ensure consistent development environments across different machines.
To get started with mise:
mise install in the project root to set up the development environment.**Environment Variab
Interact 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.