Web Fetch Server
FreeNot checkedA Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampl
About
A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.
README
An all-in-one Python MCP server for web research: fetch pages, search the web, batch-fetch, extract links, summarize via client-side sampling, and (optionally) read/write local files — all for LLM agents like Cursor. Supports local stdio and Streamable HTTP for remote access, and exercises essentially every MCP protocol capability (Tools, Resources, Prompts, Completions, Sampling, Elicitation, Roots, Progress, Logging).
Documentation:
| Document | What's inside |
|---|---|
| User Manual | Full end-user guide: install (Docker/Linux/Windows), Cursor setup, all tools, admin GUI, config, troubleshooting |
| Project Documentation | Full technical reference: architecture, modules, MCP APIs, admin API, security, Docker stack, testing |
Features
Tools
fetch_url— page content as markdown, with chunked reading (start_index,max_length)fetch_metadata_tool— HEAD request metadatabatch_fetch— fetch multiple URLs concurrently, with per-URL error isolation and progressweb_search— DuckDuckGo web search (no API key), with automatic fallback to a local SearXNG instance if DuckDuckGo's scrape failsextract_links— structured link/image extraction from a pagesummarize_url— asks the connected client's LLM to summarize a page (MCP sampling)read_file/write_file/list_dir— sandboxed local file access (opt-in, disabled by default)
Other MCP capabilities
- Resources:
config://settings,history://recent,fetch-cache://{encoded_url} - Prompts:
fetch,research_topic,summarize_page,extract_key_facts,compare_sources - Completions: URL/depth autocomplete for prompt and resource arguments
- Elicitation:
write_fileconfirms before overwriting an existing file - Roots: local file tools honor client-exposed directories in addition to
FETCH_LOCAL_FILES_ROOT - Progress notifications:
batch_fetchandsummarize_urlreport progress as they run - Management GUI: web dashboard at
/adminfor status, config, history, cache, and tools
Security
- SSRF protection with resolve-then-check and redirect re-validation
robots.txtcompliance (override withignore_robots_txt=true)- Optional domain allowlist
- Local file tools sandboxed to one configured directory, path-traversal safe
- Bearer token auth + rate limiting for HTTP mode
/healthendpoint- Windows
.exebuild (no Python required for end users)
Quick Start
Option A: Docker — full stack (recommended for server deployment)
Runs the MCP server, admin GUI, and SearXNG together.
Linux / macOS:
cd mcp-fetch-server
cp .env.docker.example .env # edit MCP_AUTH_TOKEN
chmod +x scripts/docker-up.sh
./scripts/docker-up.sh
# or: docker compose up -d --build
Windows (PowerShell):
cd "E:\my python projects\MCP\mcp-fetch-server"
copy .env.docker.example .env
.\scripts\docker-up.ps1
| Service | URL |
|---|---|
| MCP protocol | http://127.0.0.1:8000/mcp |
| Admin GUI | http://127.0.0.1:8000/admin |
| Health | http://127.0.0.1:8000/health |
| SearXNG (search fallback) | http://127.0.0.1:8080 |
Connect Cursor over HTTP (Bearer token required):
{
"mcpServers": {
"web-fetch": {
"url": "http://127.0.0.1:8000/mcp",
"headers": { "Authorization": "Bearer your-token-from-env" }
}
}
}
Local files for read_file/write_file map to the ./workspace folder on your host.
Option B: Windows executable (local / Cursor stdio)
cd "E:\my python projects\MCP\mcp-fetch-server"
.\dist\mcp-fetch-server.exe --transport stdio
Build the exe yourself: .\scripts\build_exe.ps1 → outputs dist\mcp-fetch-server.exe
Option C: Python + uv (development)
cd "E:\my python projects\MCP\mcp-fetch-server"
uv sync --dev
copy .env.example .env
uv run mcp-fetch-server --transport stdio
Connect to Cursor
See the User Manual — Connect to Cursor for step-by-step instructions.
Minimal .cursor/mcp.json using the executable:
{
"mcpServers": {
"web-fetch": {
"command": "E:/my python projects/MCP/mcp-fetch-server/dist/mcp-fetch-server.exe",
"args": ["--transport", "stdio"],
"env": { "PYTHONIOENCODING": "utf-8" }
}
}
}
Management GUI
A built-in web dashboard lets you monitor and manage the server without using Cursor:
| Mode | URL |
|---|---|
| stdio (Cursor default) | http://127.0.0.1:8001/admin |
| streamable-http | http://127.0.0.1:8000/admin (same port as MCP) |
The dashboard shows uptime, registered tools, redacted configuration, recent fetch history, cached page previews, and a button to clear history/cache. It auto-refreshes every 30 seconds.
If MCP_AUTH_TOKEN is set, enter it in the dashboard's auth bar (stored in your
browser session only). Disable the GUI with FETCH_ADMIN_ENABLED=false.
Optional: SearXNG search fallback
web_search uses DuckDuckGo by default and falls back to SearXNG when that scrape fails.
When you use Docker (docker compose up), SearXNG is started automatically and the MCP
container is preconfigured to reach it at http://searxng:8080.
For local (non-Docker) use, you can still run only SearXNG:
docker compose up -d searxng
Set FETCH_SEARXNG_URL=http://localhost:8080 in .env. See searxng/settings.yml.
Remote HTTP Mode (without full Docker stack)
$env:MCP_AUTH_TOKEN = "your-long-random-token"
.\dist\mcp-fetch-server.exe --transport streamable-http --host 127.0.0.1 --port 8000
- MCP endpoint:
http://127.0.0.1:8000/mcp - Health check:
http://127.0.0.1:8000/health
Project Structure
mcp-fetch-server/
├── dist/mcp-fetch-server.exe # Windows executable
├── src/mcp_fetch_server/ # Source code (tools, resources, prompts, security, ...)
├── tests/ # 84 pytest tests
├── docs/ # User manual + technical docs
├── scripts/docker-up.sh # Linux/macOS stack startup
├── scripts/docker-up.ps1 # Windows stack startup
├── docker-compose.yml # Full stack: MCP server + SearXNG
├── .env.docker.example # Environment template for Docker Compose
├── Dockerfile # MCP server image
├── workspace/ # Host folder mounted for local file tools (Docker)
├── searxng/settings.yml # SearXNG config (JSON API enabled)
├── src/mcp_fetch_server/admin.py # Management web GUI
└── .cursor/mcp.json # Cursor config
Development
uv run pytest
uv run ruff check .
./scripts/docker-up.sh # Linux / macOS
docker compose down
Windows only:
.\scripts\build_exe.ps1
.\scripts\docker-up.ps1
License
MIT
Install Web Fetch Server in Claude Desktop, Claude Code & Cursor
unyly install mcp-web-fetch-serverInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add mcp-web-fetch-server -- uvx mcp-fetch-serverFAQ
Is Web Fetch Server MCP free?
Yes, Web Fetch Server MCP is free — one-click install via Unyly at no cost.
Does Web Fetch Server need an API key?
No, Web Fetch Server runs without API keys or environment variables.
Is Web Fetch Server hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Web Fetch Server in Claude Desktop, Claude Code or Cursor?
Open Web Fetch Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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