MyWebSearch MCP
Enables AI agents to perform unified web research through a single MCP server, including search, page fetching, recursive crawling, document parsing, YouTube transcript extraction, and deep multi-query research.
README
<div align="center">
<img src="./assets/mywebsearch-logo.png" alt="WebSearch Forge logo" width="148" height="148">
WebSearch Forge MCP
A lightweight, unified WebSearch MCP for AI agents.
Search, read, crawl, parse, and research the public web through one MCP server.
Quick Start · Tools · Architecture · Configure Engines · 中文文档
</div>
What It Is
WebSearch Forge MCP is a self-contained MCP service for agent-driven web research:
Question → search sources → fetch pages → extract content → crawl related pages → compile evidence
It is split into clear layers:
transportsexposes MCP stdio and the optional FastAPI adapter.corehandles configuration, caching, security checks, orchestration, and research workflows.providersimplement search, fetching, extraction, crawling, and media features.- SearXNG is the single search gateway for Bing, Baidu, Brave, DuckDuckGo, and other configured engines.
Highlights
One MCP server, six capabilities
Connect once to transports/mcp_stdio.py:
| Tool | Purpose |
|---|---|
search_web |
Find candidate sources through SearXNG |
fetch_web_content |
Fetch and extract one public URL |
search_and_fetch |
Search, then read the top results |
deep_research |
Run multiple searches and compile a report |
crawl_site |
Recursively crawl a bounded same-domain site |
youtube_transcript |
Retrieve YouTube captions |
Unified search gateway
The engines argument is passed to SearXNG as a filter. WebSearch Forge does not independently fan out to search websites:
WebSearch Forge MCP → SearXNG → Bing / Baidu / Brave / DuckDuckGo
Lightweight by default
MCP stdio needs no exposed application port or database server. The cache is SQLite. Optional packages add Trafilatura, Readability, stealth requests, Playwright, Office/PDF parsing, Scrapy, YouTube captions, and FastAPI without changing the MCP contract.
Bounded crawling
crawl_site supports a zero-dependency native backend and an optional Scrapy backend. It enforces page and depth limits, stays on the starting host, resolves relative links, and isolates page failures.
Quick Start
The following commands are for Windows PowerShell.
Install
cd D:\my-websearch\my_websearch
py -3.12 -m pip install -r requirements.txt
Start SearXNG
docker version
cd D:\my-websearch\my_websearch
docker compose up -d searxng
docker compose ps
The default gateway is http://127.0.0.1:8080. Configuration lives in config/searxng/settings.yml.
Configure the MCP client
Use mcp_config.example.json and keep an absolute path:
{
"mcpServers": {
"websearch-forge": {
"command": "py",
"args": [
"-3.12",
"D:\\my-websearch\\my_websearch\\transports\\mcp_stdio.py"
],
"env": {
"SEARXNG_URL": "http://127.0.0.1:8080",
"CACHE_TTL": "300"
}
}
}
}
The stdio adapter forces UTF-8 on Windows. Loopback traffic bypasses machine-wide proxy variables by default; set PROXY_URL explicitly when needed.
Tools
search_web
Search through SearXNG without downloading page bodies.
{
"name": "search_web",
"arguments": {
"query": "Python 3.14 new features",
"engines": ["bing", "baidu", "brave"],
"limit": 5,
"time_range": "month"
}
}
fetch_web_content
Fetch and extract one public URL. HTML, PDF, DOCX, XLSX, PPTX, CSV, Markdown, and plain text are supported.
{
"name": "fetch_web_content",
"arguments": {
"url": "https://www.python.org",
"max_chars": 10000,
"stealth_mode": "off",
"render_mode": "auto",
"extraction_mode": "auto"
}
}
The response includes final URL, HTTP status, title, extraction method, word count, content, and discovered links.
search_and_fetch
Search first, then fetch the top results independently. A failed page is recorded on that item and does not cancel the batch.
{
"name": "search_and_fetch",
"arguments": {
"query": "FastAPI MCP server",
"limit": 3,
"max_chars": 12000
}
}
deep_research
Run related queries concurrently, fetch the strongest results, and return a Markdown report with source-level failures.
{
"name": "deep_research",
"arguments": {
"queries": ["SearXNG engine configuration", "MCP stdio deployment"],
"breadth": 3,
"max_chars": 12000
}
}
crawl_site
Crawl a same-host site with hard page and depth limits.
{
"name": "crawl_site",
"arguments": {
"url": "https://www.python.org",
"max_pages": 10,
"max_depth": 2,
"backend": "native",
"stealth_mode": "off"
}
}
native is the default. Install Scrapy and set backend to scrapy to use the optional backend. Each page reports URL, depth, status, fetch method, title, content, and word count.
youtube_transcript
Retrieve YouTube captions with optional source and translation languages.
Response Shape
{
"query": "OpenAI",
"provider": "searxng",
"engines": ["bing", "baidu", "brave"],
"total_results": 3,
"results": [
{
"title": "OpenAI | Research & Deployment",
"url": "https://openai.com/",
"description": "...",
"source": "openai.com",
"engine": "bing",
"score": 1.0
}
],
"partial_failures": []
}
Successful partial results are preserved. Engine, page, and document errors are returned as structured failure entries.
Architecture
flowchart LR
A[Agent / MCP Client] -->|stdio JSON-RPC| B[transports/mcp_stdio.py]
B --> C[core/service.py]
C --> D[providers/search]
D --> E[SearXNG]
E --> F[Bing / Baidu / Brave / DDG]
C --> G[providers/content]
G --> H[HTTP / stealth / Playwright]
C --> I[providers/crawl]
C --> J[providers/media]
C --> K[(SQLite TTL cache)]
transportsadapts protocols; MCP and FastAPI share the same service.coreowns orchestration, cache policy, configuration, and URL security.providers/searchtalks to SearXNG and validates engine names.providers/contenthandles HTTP, stealth transport, rendering, and extraction.providers/crawlcontains native and Scrapy crawling backends.providers/mediacontains the YouTube transcript provider.
Configure Search Engines
The project-owned SearXNG source is:
config/searxng/settings.yml
Two settings decide whether an engine can be called:
settings.ymlenables the engine inside SearXNG.providers/search/registry.pylists the accepted name inSUPPORTED_ENGINES.
Restart after changes:
cd D:\my-websearch\my_websearch
docker compose up -d --force-recreate searxng
If SearXNG does not provide the engine yet, implement that SearXNG engine first.
Security and Reliability
- Only HTTP and HTTPS URLs are accepted.
- Localhost, loopback, private IPv4, link-local, and private IPv6 targets are rejected.
- Redirect destinations are validated again.
- Search and fetch operations use a SQLite TTL cache, 300 seconds by default.
- Partial failures do not discard successful work.
- stdout is reserved for MCP JSON-RPC.
Optional Capabilities
| Capability | Enablement |
|---|---|
| Trafilatura / Readability | Install requirements-api.txt |
| Stealth requests | Install curl-cffi and use stealth_mode=high |
| JavaScript rendering | Install Playwright and use render_mode=browser |
| PDF / DOCX / XLSX / PPTX | Install matching document packages |
| Scrapy crawling | Install Scrapy and use backend=scrapy |
| FastAPI HTTP service | Run py -3.12 -m transports.api |
| YouTube captions | Install youtube-transcript-api |
Project Layout
my_websearch/
├── assets/ # Project logo
├── config/searxng/ # SearXNG settings.yml
├── core/ # Config, cache, security, orchestration
├── providers/
│ ├── search/ # SearXNG gateway and engine allow-list
│ ├── content/ # Requests, rendering, extraction
│ ├── crawl/ # Native and Scrapy backends
│ └── media/ # YouTube transcript provider
├── transports/ # MCP stdio and FastAPI adapters
├── tests/ # Dependency-free self-checks
├── docker-compose.yml # Local SearXNG gateway
├── mcp_config.example.json # MCP client template
├── requirements.txt # Dependency entry point
├── README.md # English documentation
└── README.zh-CN.md # 中文文档
Development Check
cd D:\my-websearch
py -3.12 -m my_websearch.tests.test_server
Expected output:
my_websearch self-check: ok
Optional FastAPI service:
cd D:\my-websearch\my_websearch
py -3.12 -m transports.api
Then open http://127.0.0.1:8787/docs.
License
No license is imposed yet. Add a root-level LICENSE file before public distribution.
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.