Web Search MCP
This MCP server connects an LLM to live web sources, providing real-time web search, content extraction, and specialized searches across multiple platforms, along with AI-powered research capabilities.
Web Search: Search the web or news via DuckDuckGo, with filters for time range, region, safe search, and output format (markdown or JSON).
Fetch Page: Extract clean, readable text from any URL, stripping ads and clutter, with automatic bot-detection bypass via
curlfallback.Site-Specific Search: Search a specific domain (e.g.,
docs.python.org,stackoverflow.com) for targeted documentation or site content.Reddit Search: Find real discussions and community sentiment.
Hacker News Search: Discover developer opinions and tech discourse.
GitHub Search: Find issues, pull requests, and bug reports across repositories.
X/Twitter Search: Access real-time posts and breaking news (requires session cookies).
Prediction Market Search: Query Polymarket for odds and crowd-sourced probability estimates.
AI-Powered Research: Use Groq models to browse multiple pages, validate findings, and analyze articles in depth.
Tools can be chained in a discover → read → validate workflow for reliable, well-sourced results.
Provides web and news search capabilities using DuckDuckGo, supporting text and news search with configurable parameters such as region, time range, and result format.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Web Search MCPsearch for latest AI news"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Web Search MCP
A comprehensive Model Context Protocol (MCP) server built with FastMCP that provides LLMs with real-time, high-fidelity access to the web. This server aggregates multiple search engines, social platforms, and developer tools into a single interface, allowing AI agents to perform deep research, track community sentiment, and analyze technical documentation.
Design docs → wiki — tool selection guide, decision matrix, recommended workflows, tools status & known quirks, plugin setup, and development standards.
🚀 Features
The server provides a diverse suite of tools categorized by their primary use case:
🌐 General Web Search & Retrieval
Tool | Description | Best For |
| Fast web search via DuckDuckGo or Exa (SDK). Supports domain-scoping, date filtering, news mode, and geographic region. Default auto-provider tries DDG first, falls back to Exa. | Quick lookups, high-volume searches, pagination, broad coverage |
| High-fidelity text extraction from URLs with bot-detection bypass, SSRF protection (blocks private/internal IPs), and multiple output formats. | Deep reading of search results, standalone URL fetching |
💬 Social & Community Intelligence
Tool | Description | Best For |
| Keyless search for community discussions, opinions, and real-world user experiences via RSS + Shreddit enrichment. | Product reviews, community sentiment, troubleshooting |
| Technical discourse, startup news, and developer opinions via the Algolia HN API. | Tech news, startup discussions, developer opinions |
| Search for Issues and PRs to track bugs, feature requests, and community sentiment. Requires | Bug tracking, feature requests, community sentiment |
| Fetch full conversation threads from GitHub Issues/PRs, sorted by reactions with author/date/reactions metadata. | Deep-diving into specific issues/PRs |
| Real-time discourse and breaking news via Xquik API or vendored Bird CLI (requires session cookies or API key). | Breaking news, community reactions, engagement signals |
| Search people, companies, jobs, posts via DuckDuckGo + Jina Reader (r.jina.ai). No API key needed. | Professional profiles, company research, job search |
🎓 Academic & Reference
Tool | Description | Best For |
| Specialized search for academic papers with Lucene field prefixes ( | Research papers, citations, literature reviews |
| Factual summaries and background research via the MediaWiki API. | Factual summaries, background research, citations |
Related MCP server: DuckDuckGo MCP Server
📋 Prerequisites
Requirement | Version | Notes |
Python | 3.11+ | Required |
Latest | Recommended for installation and environment management |
Optional External Tools
Tool | Required For | Installation |
| Authenticated GitHub search & issue retrieval (higher rate limits) |
|
Node.js | Vendored Bird CLI for X/Twitter search (not needed with | 22+ recommended; |
⚙️ Installation
You have three options depending on your use case:
Option A: Quick Run (via uvx)
Fastest way to try it out without cloning the repo. Add to your MCP client config:
{
"mcpServers": {
"web-search": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/sydasif/web-search-mcp.git",
"web-search-mcp"
]
}
}
}Option B: Permanent Install
Fastest startup times with a globally installed tool:
uv tool install git+https://github.com/sydasif/web-search-mcp.gitThen configure your MCP client:
{
"mcpServers": {
"web-search": {
"command": "web-search-mcp"
}
}
}Option C: Development Install
If you want to modify the code or contribute:
git clone https://github.com/sydasif/web-search-mcp.git
cd web-search-mcp
uv sync
uv run web-search-mcpVerify It's Working
Once the server is running, try a simple search:
search_web(query="current weather in Tokyo")🔐 Configuration & Authentication
Most tools work out of the box with zero configuration. The following environment variables are only needed for premium or authenticated features.
Environment Variables Reference
Variable | Required For | How to Get It |
| Exa AI semantic search (optional fallback) | Sign up at exa.ai |
| Higher GitHub API rate limits (optional) | Generate a GitHub PAT |
| X/Twitter search via Bird CLI (required) | Session cookie from x.com (see below) |
| X/Twitter search via Bird CLI (required) | Session cookie from x.com (see below) |
| X/Twitter search via Xquik API (alternative to cookies) | Sign up at xquik.ai |
Setting Up GitHub Authentication
Option 1 — Recommended: Use gh CLI
gh auth loginThe server detects your local session automatically.
Option 2: Manual Token
export GITHUB_TOKEN="ghp_your_token_here"Setting Up X/Twitter Authentication
X/Twitter search requires either session cookies or an API key.
Option 1 — Session Cookies (Bird CLI):
Log into
x.comin your browser.Open DevTools (F12) → Application (or Storage) → Cookies →
x.com.Copy the values for
auth_tokenandct0.Export them in the shell where the MCP server runs:
export AUTH_TOKEN="your_auth_token" export CT0="your_ct0"Note: These are session cookies. If searches return 401s, refresh them by logging out and back in.
Option 2 — Xquik API Key (Recommended):
Sign up at xquik.ai to get an API key.
Export it:
export XQUIK_API_KEY="your_xquik_key"This bypasses the Node.js Bird CLI dependency entirely.
Setting Up Exa AI (Optional)
Exa provides semantic search and JS-heavy page fallback:
export EXA_API_KEY="your_exa_key"💡 Usage Examples
Web Research
# Broad search
search_web(query="Latest NVIDIA H200 benchmarks")
# Targeted documentation search
search_web(query="useEffect cleanup", domain="react.dev")
# News with region filter
search_web(query="elections", search_type="news", region="us-en", provider="exa")
# Date-filtered search
search_web(query="uv package manager", time_range="w", provider="auto")
# Deep read a page
fetch_page(url="https://docs.python.org/3/library/os.html")Technical Analysis
# Track GitHub issues/PRs
search_github(query="uv package manager")
# Get full GitHub issue thread
get_github_issue(url="https://github.com/astral-sh/uv/issues/1")Community Sentiment
# Reddit discussions
search_reddit(query="Best mechanical keyboards 2024", subreddits=["MechanicalKeyboards"])
# Hacker News technical discourse
search_hackernews(query="MCP server architecture")
# LinkedIn professional search
search_linkedin(query="site reliability engineer", content_type="people")
search_linkedin(query="machine learning startup", content_type="companies")
search_linkedin(query="kubernetes devops", content_type="jobs")
search_linkedin(query="AI agents", content_type="posts")Academic Research
# arXiv paper search with field prefixes
search_arxiv(query="au:Goodfellow AND cat:cs.LG")
search_arxiv(query="transformer attention", sort_by="submitted_date")
# Wikipedia background research
search_wikipedia(query="Quantum computing")🏗️ Project Structure
web_search_mcp/
├── server.py # Entry point: FastMCP init, @mcp.tool registrations
├── search/ # Search engine implementations
│ ├── ddg.py # DuckDuckGo search + trafilatura page fetch
│ └── exa.py # Exa SDK search & content fetch (lazy-init client)
├── social/ # Community platform integrations
│ ├── github.py # GitHub Search API + gh CLI issue rendering
│ ├── hackernews.py # Algolia HN API + comment enrichment
│ ├── linkedin/ # LinkedIn search via DDG + Jina Reader
│ │ ├── __init__.py # LinkedIn search tool registration
│ │ └── client.py # DDG search + Jina Reader enrichment
│ ├── reddit/ # RSS + Shreddit keyless pipeline
│ │ ├── client.py # HTTP client with RSS parsing
│ │ ├── parsers.py # RSS/HTML parsers
│ │ └── shreddit.py # Shreddit comment enrichment
│ └── x.py # X/Twitter search via Xquik API or vendored Bird CLI
├── tools/ # Specialized reference utilities
│ ├── arxiv.py # arXiv paper search (Lucene field prefixes)
│ └── wikipedia.py # Wikipedia MediaWiki API
├── _config/ # Settings, env vars, rate limits, depth tiers
│ ├── settings.py # pydantic-settings (EXA_API_KEY, SEARCH_MCP_ prefix)
│ └── limits.py # Per-platform quick/default/deep limits, timeouts
├── _http/ # Shared HTTP + SSRF protection
│ └── client.py # validate_url, http_client, get_json_client
├── _models/ # Pydantic request/response models
│ ├── requests.py # SearchRequest
│ ├── responses.py # ErrorResponse, SearchResponse, PageResponse
│ └── types.py # Depth, ResponseFormat, SearchType, FetchOutputFormat
├── _utils/ # Shared helpers
│ ├── formatting.py # Markdown formatters, date/epoch utils
│ ├── rate_limiter.py # Token-bucket rate limiter
│ └── scoring.py # Relevance scoring
└── vendor/ # Vendored third-party tools
└── bird-search/ # Node.js CLI for X/Twitter search (fallback when XQUIK_API_KEY unset)🛠️ Tool Implementation Flow
When adding a new tool:
Implement logic in the appropriate module (
search/,social/, ortools/)Define models in
_models/(request/response types)Register in
server.pyusing@mcp.tooldecorator with a clear docstring (serves as the tool's description for the LLM)
🧪 Testing
# Run all tests
uv run pytest
# Run a single test file
uv run pytest tests/test_module.py
# Run a specific test
uv run pytest tests/test_module.py::test_function_name
# Run with coverage
uv run pytest --cov=web_search_mcp🔧 Troubleshooting
Problem | Likely Cause | Solution |
Auth errors on a tool | Env var not set in the server's shell | Export the variable in the same shell where the MCP server process runs |
GitHub returns empty results | Not authenticated | Run |
| Expired X session cookies | Re-extract |
| Bot detection | Try |
| Upstream arXiv maintenance | Wait a few minutes and retry |
Tool says "Query cannot be empty" | Missing or blank query | Provide a non-empty search query |
🤝 Contributing
Fork the repository.
Create a feature branch:
git checkout -b feat/my-new-toolEnsure all tests pass:
uv run pytestSubmit a pull request with a detailed description of the changes.
📄 License
This project is licensed under the MIT License.
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