MCP Web Search Server

MCP Web Search Server

Enables privacy-focused web searches, social media lookups, and web archive retrieval across multiple engines including DuckDuckGo, Brave, Reddit, YouTube, and Wayback Machine with built-in caching and security features.

Category
Visit Server

README

📂 MCP Web Search Server

A privacy‑focused web, social media, and archive search server exposing tools via the Model Control Protocol (MCP) for controlled access to external search capabilities.


Table of Contents


🎯 Features

  • Parallel search across multiple privacy‑focused web engines.
  • Social media lookup for public content on major platforms.
  • Archive retrieval from Wayback Machine, archive.today, Google Cache and others.
  • Dynamic listing of supported engines and archive services.
  • Result caching with LRU eviction to speed up repeated queries.

📦 Installation & Quick Start

# Clone the repository (if applicable)
git clone https://github.com/undici77/MCPWebSearch.git
cd MCPWebSearch

# Run the startup script (adjust name if different)
./run.sh -d /path/to/working/directory

1️⃣ Create & activate a Python virtual environment (.venv).
2️⃣ Install all required dependencies from requirements.txt.
3️⃣ Launch the MCP Search Server (main.py) which listens on stdin/stdout for JSON‑RPC messages.

📌 Ensure the startup script is executable: chmod +x run.sh


⚙️ Command‑Line Options

Option Description
-d, --directory Path to the working directory (default: current process dir).

The server itself does not require additional CLI flags; all configuration is performed via JSON‑RPC.


🤝 Integration with LM Studio

Add an entry to your mcp.json so LM Studio can start the server automatically:

{
  "mcpServers": {
    "web-search": {
      "command": "/absolute/path/to/run.sh",
      "args": [
        "-d",
        "/absolute/path/to/working/directory"
      ],
      "env": { "WORKING_DIR": "." }
    }
  }
}

📌 Make the script executable (chmod +x /absolute/path/to/run.sh) and run ./run.sh once to install the virtual environment before launching LM Studio.


📡 MCP API Overview

All communication follows JSON‑RPC 2.0 over stdin/stdout.

initialize

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "initialize",
  "params": {}
}

Response: protocol version (2024-11-05), server capabilities (tool enumeration) and basic server info (name, version).

tools/list

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/list",
  "params": {}
}

Response: an array of tool definitions (name, description, input schema).

tools/call

{
  "jsonrpc": "2.0",
  "id": 3,
  "method": "tools/call",
  "params": {
    "name": "<tool_name>",
    "arguments": {}
  }
}

Note: The tool identifier key is name, not tool.


🛠️ Available Tools

web_search

Search the web using multiple privacy‑focused engines in parallel.

Name Type Required Description
query string Search query (max 500 characters).
engine string ❌ (default all) Engine to use (duckduckgo, brave, startpage, ecosia, mojeek, yandex or all).
max_results integer ❌ (default 20) Max results per engine (1‑50).

Example

{
  "jsonrpc": "2.0",
  "id": 10,
  "method": "tools/call",
  "params": {
    "name": "web_search",
    "arguments": {
      "query": "privacy focused search engines",
      "engine": "duckduckgo",
      "max_results": 15
    }
  }
}

The server returns a formatted text block containing titles, URLs and snippets from each selected engine.


social_search

Search public content on major social‑media platforms.

Name Type Required Description
query string Search query (max 500 characters).
platform string ❌ (default all) Platform to search (twitter, reddit, youtube, github, stackoverflow, medium, pinterest, tiktok, instagram, facebook, linkedin or all).

Example

{
  "jsonrpc": "2.0",
  "id": 11,
  "method": "tools/call",
  "params": {
    "name": "social_search",
    "arguments": {
      "query": "AI ethics research",
      "platform": "reddit"
    }
  }
}

The response contains direct URLs that can be opened in a browser.


archives_search

Find archived versions of a URL across multiple web‑archive services.

Name Type Required Description
url string Complete URL (must include http:// or https://).
service string ❌ (default all) Archive service (wayback, archive_today, google_cache, bing_cache, yandex_cache, cachedview, ghostarchive or all).
check_availability boolean ❌ (default false) When true, the server queries the Wayback Machine API for snapshot statistics.

Example

{
  "jsonrpc": "2.0",
  "id": 12,
  "method": "tools/call",
  "params": {
    "name": "archives_search",
    "arguments": {
      "url": "https://example.com",
      "service": "wayback",
      "check_availability": true
    }
  }
}

The response lists archive URLs and, if requested, snapshot counts and timestamps.


list_engines

List all available privacy‑focused search engines.

Name Type Required Description
(No parameters)

Example

{
  "jsonrpc": "2.0",
  "id": 13,
  "method": "tools/call",
  "params": {
    "name": "list_engines",
    "arguments": {}
  }
}

The server returns a markdown‑formatted overview of each engine and usage notes.


list_archives_services

List all supported web‑archive services.

Name Type Required Description
(No parameters)

Example

{
  "jsonrpc": "2.0",
  "id": 14,
  "method": "tools/call",
  "params": {
    "name": "list_archives_services",
    "arguments": {}
  }
}

The response includes a description of each service, its ID and key features.


clear_cache

Clear the internal search‑result cache.

Name Type Required Description
(No parameters)

Example

{
  "jsonrpc": "2.0",
  "id": 15,
  "method": "tools/call",
  "params": {
    "name": "clear_cache",
    "arguments": {}
  }
}

The server replies with a confirmation message.


🔐 Security Features

  • Query sanitisation – strips control characters, removes HTML tags and enforces MAX_QUERY_LENGTH (500).
  • Strict URL validation – accepts only http:// or https:// schemes with a valid domain.
  • Blocked patterns – regexes prevent <script> injection, javascript: URIs and event‑handler attributes.
  • Input schema enforcement – each tool validates required fields via the JSON‑RPC inputSchema.
  • Rate limiting – an asyncio semaphore caps concurrent external requests (MAX_CONCURRENT_SEARCHES).

© 2025 Undici77 – All rights reserved.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured