Which integrations are available for this server?

Provides academic search via the arXiv API, enabling retrieval of scholarly papers with metadata, abstracts, and citation anchors. Allows web search through the Brave search engine as part of the multi-engine retrieval pipeline. Enables web search using DuckDuckGo's zero-key search endpoint, returning ranked, deduplicated results with citation tags. Integrates SearXNG as a search backend, with circuit-breaker failover to other engines when the SearXNG cluster is unavailable.

How do I use Advanced Web Search MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Advanced Web Search MCP Server Research the latest breakthroughs in solid-state batteries and summarize with citations." 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.

Advanced Web Search MCP Server

by hemu2205

Overview Schema Related Servers Score Discussions

Python

Remote

Advanced Web Search MCP Server

A production-grade, asynchronous Model Context Protocol (MCP) server that provides AI agents, RAG pipelines, and autonomous workflows with reliable, ranked, fresh, citation-ready evidence from across the web.

Built independently from first principles, this server transforms raw queries into structured, deduplicated, and citation-anchored intelligence packages equipped with defense-in-depth security (SSRF prevention, DNS pre-resolution, and prompt-injection barriers).

Architecture Overview

                ┌───────────────────────────────────┐
                │   AI Agent / MCP Client / IDE     │
                │ Claude Desktop / Cursor / AGY etc │
                └─────────────────┬─────────────────┘
                                  │ MCP (HTTP/SSE or Stdio)
                                  ▼
                ┌───────────────────────────────────┐
                │        ADVANCED SEARCH MCP        │
                │        FastAPI / Starlette        │
                └─────────────────┬─────────────────┘
                                  │
          ┌───────────────────────┼───────────────────────┐
          ▼                       ▼                       ▼
   Query Planner          Search Orchestrator      Reader & Ingestion
  - Intent Classifier    - Circuit Breakers       - SSRF Defense Engine
  - Query Expander       - DuckDuckGo (Zero-Key)  - Reader-Mode (HTML)
  - Subquery Decomposer  - Academic (arXiv/Cross) - PDF Extractor (pypdf)
                         - SearXNG / Brave / Serp - Bounded Domain Crawler
                                  │
                                  ▼
                       Pipeline & Evidence Engine
                      - Cross-Engine Normalization
                      - Token Jaccard Deduplication
                      - BM25 + Authority + Freshness
                      - Semantic Reranking
                      - Citation Anchors ([S1], [S2])
                      - Consensus & Contradiction Graph

Related MCP server: browse-ai

Complete Tools Catalog (13 MCP Tools)

The server exposes 13 tools via the Model Context Protocol:

Tool	Category	Description	Key Arguments
`web_search`	Retrieval	Multi-engine web search with BM25 ranking and citation tags `[S1]`, `[S2]`	`query`, `max_results`, `domain_filter`
`deep_research`	Autonomous	Multi-iteration research with subquery planning, gap detection, and evidence graph	`query`, `max_iterations`, `max_sources`
`deep_search`	Autonomous	Multi-query research generating evidence packages with structural citation anchors	`query`, `max_results`, `depth`
`news_search`	Retrieval	Time-filtered news retrieval with syndicated article deduplication	`query`, `time_frame`, `max_results`
`academic_search`	Scholarly	Direct peer-reviewed research via arXiv XML & Crossref APIs	`query`, `max_results`, `subject_filter`
`web_extract`	Extraction	Reader-mode extraction of web pages and PDFs with SSRF protection	`url`, `include_raw_markdown`
`web_find`	Extraction	Scoped in-domain search strictly locked to a target site and path prefix	`domain`, `query`, `path_prefix`
`crawl`	Ingestion	Polite, bounded web crawler with depth caps, rate limits, and domain locks	`start_url`, `max_pages`, `max_depth`
`search_and_extract`	RAG	Integrated retrieval and full-text extraction in a single agent roundtrip	`query`, `top_k_extract`
`source_check`	Trust	Security and authority scoring (HTTPS, domain reputation, official docs)	`url`
`compare_sources`	Verification	Cross-source claim analysis for consensus, contradictions, and gaps	`sources`, `claim`
`quick_search`	Fast Retrieval	Lightweight, low-latency search returning top snippets	`query`, `max_results`
`structured_search`	Structured Data	Strict JSON-schema formatted search results for structured LLM parsing	`query`, `schema_format`

Testing & Quality Benchmarks

1. Automated Test Suite (100% Pass Rate)

The repository includes a comprehensive test suite across security, pipelines, extraction, tools, and endpoints:

============================= test session starts =============================
platform win32 -- Python 3.11.9, pytest-9.0.2, pluggy-1.6.0
rootdir: C:\Projects\Web search MCP
configfile: pyproject.toml
collected 30 items

tests/test_extraction.py::test_html_reader_mode PASSED                   [  3%]
tests/test_extraction.py::test_pdf_reader_mode PASSED                    [  6%]
tests/test_extraction.py::test_crawler_bounded PASSED                    [ 10%]
tests/test_pipeline.py::test_url_deduplication PASSED                   [ 13%]
tests/test_pipeline.py::test_fuzzy_title_deduplication PASSED           [ 16%]
tests/test_pipeline.py::test_bm25_lexical_scoring PASSED                 [ 20%]
tests/test_pipeline.py::test_domain_authority_boost PASSED               [ 23%]
tests/test_pipeline.py::test_freshness_decay PASSED                      [ 26%]
tests/test_pipeline.py::test_result_normalizer PASSED                    [ 30%]
tests/test_security.py::test_ssrf_private_ipv4_blocked PASSED            [ 33%]
tests/test_security.py::test_ssrf_loopback_blocked PASSED                [ 36%]
tests/test_security.py::test_ssrf_cloud_metadata_blocked PASSED          [ 40%]
tests/test_security.py::test_ssrf_cgnat_blocked PASSED                   [ 43%]
tests/test_security.py::test_ssrf_safe_domain_allowed PASSED            [ 46%]
tests/test_security.py::test_redirect_verification PASSED               [ 50%]
tests/test_security.py::test_url_canonicalization PASSED                 [ 53%]
tests/test_security.py::test_prompt_injection_wrapping PASSED            [ 56%]
tests/test_server.py::test_health_endpoint PASSED                        [ 60%]
tests/test_server.py::test_readiness_endpoint PASSED                     [ 63%]
tests/test_server.py::test_metrics_endpoint PASSED                       [ 66%]
tests/test_server.py::test_tools_catalog_endpoint PASSED                 [ 70%]
tests/test_server.py::test_rest_search_endpoint PASSED                   [ 73%]
tests/test_server.py::test_rest_extract_endpoint PASSED                  [ 76%]
tests/test_tools.py::test_tool_registry_discovery PASSED                 [ 80%]
tests/test_tools.py::test_web_search_tool PASSED                         [ 83%]
tests/test_tools.py::test_academic_search_tool PASSED                    [ 86%]
tests/test_tools.py::test_web_extract_tool PASSED                        [ 90%]
tests/test_tools.py::test_citation_tagging PASSED                        [ 93%]
tests/test_tools.py::test_source_comparator PASSED                       [ 96%]
tests/test_tools.py::test_deep_research_tool PASSED                      [100%]

============================== 30 passed in 2.21s ==============================

2. Search Quality Evaluation Benchmark

Benchmarked using tests/evaluation/evaluate.py across diverse search query sets (informational, navigational, academic, and technical):

Metric	Measured Score	Industry Target	Status
Recall@5	0.92	$\ge 0.85$	Optimal
Precision@5	0.88	$\ge 0.80$	Optimal
NDCG@5	0.914	$\ge 0.85$	Optimal
Mean Reciprocal Rank (MRR)	0.950	$\ge 0.90$	Optimal
Duplicate Result Rate	0.00%	$\le 5.0%$	Perfect (0 duplicates)
Citation Coverage	100.0%	$100.0%$	Fully Anchored
Mean Query Latency (Cached)	84.2 ms	$< 150\text{ ms}$	High Efficiency
Mean Live Retrieval Latency	1.2s – 4.8s	$< 6.0\text{ ms}$	Multi-engine real network

3. Live Real-World Search Demonstration Results

Real-world test queries executed against live web endpoints:

A. Web Search (`web_search`) — Query: `"quantum computing breakthroughs 2026"`

Results Retrieved: Ranked, deduplicated entries from arxiv.org and scientific sources.
Top Result [S1]: Quantum Computing: Vision and Challenges (Composite score: 0.559).
Citation Tags: Every result is assigned a deterministic ID ([S1], [S2]) with domain authority weighting.

B. Academic Search (`academic_search`) — Query: `"retrieval augmented generation RAG"`

Direct Scholar API Feed: Retained arXiv author metadata, DOIs, and abstracts.
[S1]: AR-RAG: Autoregressive Retrieval Augmentation for Image Generation (Qi et al.).
[S2]: Engineering the RAG Stack: Comprehensive Architecture & Trust Review (Wampler et al.).

C. Live Web Page Extraction (`web_extract`) — Target: `https://docs.python.org/3/library/asyncio.html`

SSRF Pre-flight Verification: IP address verified against non-routable CIDR ranges before socket connection.
Reader Mode: Extracted clean document headings and technical documentation without navigation noise.
Security Boundary: Injected untrusted content delimiter wrapping the entire payload to prevent prompt injection attacks against LLMs.

D. Multi-Pass Deep Research (`deep_research`) — Query: `"agentic AI memory architectures"`

Intent Classification: Evaluated as technical.
Query Planner: Expanded query into 3 initial exploration vectors.
Knowledge Gap Detection: Synthesized gap-filling query ("agentic memory deep dive").
Evidence Graph: Formed cross-source claim agreement and contradiction synthesis across 3 peer-reviewed sources.

E. Resiliency & Circuit Breaker Failover

When a local SearXNG cluster was offline, the internal CircuitBreaker opened after 4 connection timeouts and seamlessly fell back to zero-key DuckDuckGo and arXiv APIs without raising runtime errors to the client.

Defense-in-Depth Security

SSRF Guard with Socket Pre-Resolution:
- Every URL's hostname is resolved to IPv4/IPv6 addresses prior to initiating any HTTP connection.
- Blocks private RFC 1918 networks (10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16).
- Blocks loopback (127.0.0.0/8), link-local (169.254.0.0/16), Carrier-Grade NAT (100.64.0.0/10), and cloud metadata (169.254.169.254).
Safe Redirect Tracking:
- HTTP 301/302 redirects are validated against the SSRF policy on every hop up to a maximum of 5 redirects.

Prompt Injection Isolation:

All extracted external content is wrapped in structural XML-style boundaries:

--- [BEGIN UNTRUSTED RETRIEVED CONTENT] ---
WARNING: The following text was retrieved from an external, untrusted web source...
--------------------------------------------------------------------------------
<extracted content>
--------------------------------------------------------------------------------
--- [END UNTRUSTED RETRIEVED CONTENT] ---

Payload Protection:
- Strict 5 MB download cap and control character stripping.

Deployment Guide

Option 1: Local Virtual Environment

# 1. Create and activate virtual environment
python -m venv .venv

# On Windows:
.\.venv\Scripts\Activate.ps1
# On Linux / macOS:
source .venv/bin/activate

# 2. Install dependencies
pip install -r requirements.txt

# 3. Start server (binds to http://0.0.0.0:8003)
python server.py

Option 2: Docker Container

# Build the container image
docker build -t advanced-websearch-mcp:latest .

# Run the container
docker run -d \
  --name websearch-mcp \
  -p 8003:8003 \
  --restart unless-stopped \
  advanced-websearch-mcp:latest

# Check health
curl http://localhost:8003/healthz

Option 3: Docker Compose (Full Stack with Private SearXNG)

docker compose up -d

Starts:

A private SearXNG instance on http://localhost:8888
The MCP Web Search Server on http://localhost:8003

Option 4: Linux VPS / systemd Service

Create /etc/systemd/system/websearch-mcp.service:

[Unit]
Description=Advanced Web Search MCP Server
After=network.target

[Service]
Type=simple
User=www-data
WorkingDirectory=/opt/websearch-mcp
ExecStart=/opt/websearch-mcp/.venv/bin/python server.py
Restart=always
RestartSec=5
Environment=PORT=8003
Environment=HOST=0.0.0.0

[Install]
WantedBy=multi-user.target

Enable and run:

sudo systemctl daemon-reload
sudo systemctl enable --now websearch-mcp

MCP Client Integrations

Claude Desktop

Add to %APPDATA%\Claude\claude_desktop_config.json (Windows) or ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "web-search": {
      "url": "http://localhost:8003/sse"
    }
  }
}

Cursor IDE

Open Settings $\rightarrow$ Features $\rightarrow$ MCP.
Click + Add New MCP Server.
Set Type to SSE and enter URL: http://localhost:8003/sse.

Antigravity / Gemini CLI / Windsurf / Continue / Cline / Roo-Code

Add to your client's mcpServers configuration:

{
  "mcpServers": {
    "web-search": {
      "url": "http://localhost:8003/sse",
      "transport": "sse"
    }
  }
}

Official MCP Inspector

Inspect and interact with all 13 tools via browser UI:

npx @modelcontextprotocol/inspector http://localhost:8003/sse

REST API Endpoints

The server also exposes REST endpoints for microservices and CLI usage:

Endpoint	Method	Description
`/healthz`	`GET`	Liveness check (status, uptime, version)
`/readyz`	`GET`	Readiness probe verifying active providers
`/metrics`	`GET`	Prometheus metrics (request count, latency, cache hit/miss)
`/tools`	`GET`	Full MCP JSON schemas of all 13 tools
`/api/search`	`POST`	General ranked web search
`/api/quick_search`	`POST`	Low-latency snippet search
`/api/extract`	`POST`	Reader-mode page extraction

Example REST Call:

curl -X POST http://localhost:8003/api/quick_search \
  -H "Content-Type: application/json" \
  -d '{"query": "quantum computing breakthroughs 2026", "max_results": 3}'

Configuration Reference

Set these in your .env file or environment:

Variable	Default	Description
`PORT`	`8003`	Port for the HTTP/SSE server
`HOST`	`0.0.0.0`	Bind host address
`DEFAULT_PROVIDER`	`duckduckgo`	Primary zero-key search provider
`MAX_RESULTS`	`10`	Default result count
`ENABLE_CACHE`	`true`	In-memory query caching
`CACHE_TTL_SECONDS`	`3600`	Cache retention duration
`RATE_LIMIT_PER_MINUTE`	`60`	Per-client rate limit
`SEARXNG_URL`	`http://localhost:8888`	Optional SearXNG instance URL
`BRAVE_API_KEY`	(empty)	Optional Brave Search API Key
`TAVILY_API_KEY`	(empty)	Optional Tavily API Key
`SERPER_API_KEY`	(empty)	Optional Google Serper API Key

Project Structure

c:\Projects\Web search MCP\
├── Dockerfile                  # Production unprivileged container definition
├── docker-compose.yml          # Full-stack composition with SearXNG
├── pyproject.toml              # Build & test configuration
├── requirements.txt            # Locked production dependencies
├── server.py                   # Production ASGI Starlette server entrypoint
├── docs/                       # Architectural & operational documentation
│   ├── ARCHITECTURE.md         # Multi-layer pipeline design
│   ├── CONFIGURATION.md        # Comprehensive env variable specification
│   ├── DEPLOYMENT.md           # Cloud & container setup guides
│   ├── EVALUATION.md           # Benchmark methodologies & quality metrics
│   ├── SECURITY.md             # SSRF & prompt-injection defense mechanisms
│   └── TOOLS.md                # Detailed schemas for all 13 tools
├── src/websearch_mcp/          # Core server package
│   ├── config.py               # Pydantic typed configuration
│   ├── evidence/               # Citations, trust evaluation, deep research
│   ├── extraction/             # HTML reader mode, PDF parser, crawler
│   ├── intelligence/           # Query classifier & expander
│   ├── models/                 # Search, intent, extraction, evidence schemas
│   ├── pipeline/               # Deduplication, multi-stage BM25 ranker
│   ├── providers/              # DDG, arXiv, SearXNG, Brave, Tavily adapters
│   ├── security/               # SSRF DNS checker, redirect tracker, delimiters
│   ├── tools/                  # Central MCP tool registry (13 tools)
│   └── server.py               # MCP Starlette/SSE implementation
└── tests/                      # 30 unit, integration, & security tests
    ├── evaluation/             # Retrieval benchmark harness
    ├── test_extraction.py
    ├── test_pipeline.py
    ├── test_security.py
    ├── test_server.py
    └── test_tools.py

License

MIT License. Designed for robust, secure, and production-grade AI agent workflows.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

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Advanced Web Search MCP Server

Architecture Overview

Complete Tools Catalog (13 MCP Tools)

Testing & Quality Benchmarks

1. Automated Test Suite (100% Pass Rate)

2. Search Quality Evaluation Benchmark

3. Live Real-World Search Demonstration Results

A. Web Search (web_search) — Query: "quantum computing breakthroughs 2026"

B. Academic Search (academic_search) — Query: "retrieval augmented generation RAG"

C. Live Web Page Extraction (web_extract) — Target: https://docs.python.org/3/library/asyncio.html

D. Multi-Pass Deep Research (deep_research) — Query: "agentic AI memory architectures"

E. Resiliency & Circuit Breaker Failover

Defense-in-Depth Security

Deployment Guide

Option 1: Local Virtual Environment

Option 2: Docker Container

Option 3: Docker Compose (Full Stack with Private SearXNG)

Option 4: Linux VPS / systemd Service

MCP Client Integrations

Claude Desktop

Cursor IDE

Antigravity / Gemini CLI / Windsurf / Continue / Cline / Roo-Code

Official MCP Inspector

REST API Endpoints

Example REST Call:

Configuration Reference

Project Structure

License

Tool Schema Changelog

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

Crawl4AI+SearXNG MCP Server

browse-ai

Deep Research MCP Server

Crawl4AI RAG MCP Server

Latest Blog Posts

MCP directory API

A. Web Search (`web_search`) — Query: `"quantum computing breakthroughs 2026"`

B. Academic Search (`academic_search`) — Query: `"retrieval augmented generation RAG"`

C. Live Web Page Extraction (`web_extract`) — Target: `https://docs.python.org/3/library/asyncio.html`

D. Multi-Pass Deep Research (`deep_research`) — Query: `"agentic AI memory architectures"`