SSMCP
Supports OAuth authentication using Authentik as an identity provider for secure access to the MCP server.
Used for optional Web UI monitoring, storing request and response data for debugging and inspection purposes.
Integrates with SearXNG to provide web search capabilities, aggregating results from multiple search engines and returning clean content in Markdown.
Allows extraction of subtitles and timestamps from YouTube videos, enabling AI models to access and analyze video content.
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., "@SSMCPsearch for latest AI news and summarize"
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.
SSMCP - Super Simple MCP Server
Model Context Protocol (MCP) server providing web search with content extraction.
Why Use SSMCP?
Many AI models, especially local models or certain cloud-based models, don't have built-in web browsing capabilities. SSMCP bridges that gap by providing a simple, self-hosted solution that gives your AI assistant the ability to:
Search and Read the Web: Let your AI search for current information, read articles, documentation, or any web content
Extract Clean Content: Automatically converts messy web pages into clean Markdown format that AI models can easily understand
Access YouTube Transcripts: Extract subtitles from videos with timestamps for analysis or summarization
AI-Powered Summarization: Optional LLM summarization extracts only relevant information from web pages based on your search query
Privacy-Focused: Self-hosted solution - your searches and browsing stay on your infrastructure
Works with Any Model: Compatible with local models (like Qwen, Llama) and cloud APIs (DeepSeek, Claude, GPT) that support MCP
Example Use Cases:
Research recent news or developments on a topic
Read and summarize technical documentation
Analyze current market trends or product reviews
Extract information from YouTube tutorials or presentations
Get up-to-date answers that aren't in the model's training data
Get concise, query-relevant summaries of web content (with LLM summarization enabled)
Related MCP server: ORZ MCP
Features
Web Search: Search the web and get results with extracted content in Markdown
Web Fetch: Fetch and extract content from any URL as clean Markdown
YouTube Subtitles: Extract subtitles and timestamps from YouTube videos
LLM Summarization (Optional): Use an LLM to summarize and filter search results by relevance to your query
Powered by: SearXNG for search, Crawl4AI for content extraction, yt-dlp for subtitles
Simple API: Easy-to-use interface designed for compatibility with both small local models(like Qwen3 30b) and cloud models lacking web capabilities (e.g., DeepSeek 3.2)
Container Support: Full containerized deployment with Docker Compose
Quick Start
Prerequisites
Docker
Docker Compose
1. Clone this repository
git clone https://github.com/antonsokolskyy/SSMCP.git2. Create .env file
cd SSMCP/
cp .env.example .env3. Set Up SearXNG
Start and stop the searxng container to generate settings.yml:
docker compose up searxngWait until you see:
"/etc/searxng/settings.yml" does not exist, creating from template...Then press Ctrl+C to stop it.
Edit deploy/docker/searxng_data/settings.yml and add json to the formats list:
# remove format to deny access, use lower case.
# formats: [html, csv, json, rss]
formats:
- html
- json4. Build the SSMCP image
docker compose build5. Run the Full Stack
docker compose up -dYouTube Cookies (Optional)
To access age-restricted or private YouTube videos, and to reduce the chances of hitting captchas or IP blocking, you can provide cookies from your browser.
Note: The cookies file must be in Netscape cookie format.
Option 1: Using Browser Extension
Install an extension (like "Get cookies.txt LOCALLY") for your browser and export cookies for youtube.com in Netscape format.
Option 2: Using yt-dlp Binary
yt-dlp --cookies-from-browser chrome --cookies cookies.txt https://www.youtube.com/watch?v=VIDEO_ID Replace chrome with your browser (firefox, edge, safari, etc.). This automatically exports in Netscape format.
Place the generated cookies.txt file in:
deploy/docker/ssmcp/cookies.txtSecurity Warning: The cookies file contains authentication tokens and sensitive data. Set appropriate file permissions to prevent unauthorized access:
chmod 600 deploy/docker/ssmcp/cookies.txtThe file will be automatically detected and used by Docker container.
MCP URL
The server uses Streamable HTTP transport. Connect to the MCP server at:
http://{HOST}:{PORT}/mcpExample:
http://localhost:8000/mcpUsage with MCP Clients
LM Studio
{
"mcpServers": {
"ssmcp": {
"url": "http://localhost:8000/mcp"
}
}
}Web UI
SSMCP includes an optional Web UI for monitoring requests and responses. This is particularly useful for debugging and inspecting how the model uses the tools.
Configure Redis: Open your
.envfile and uncomment theREDIS_URLline:
REDIS_URL=redis://redis:6379Enable Services: Open
docker-compose.yml(anddocker-compose.dev.ymlif using development mode) and uncomment theredisandssmcp-uiservice blocks.Restart Services:
make buildAccess the Monitor: Open http://localhost:8081 in your browser.
Tools
web_search
Performs a web search and returns relevant results with extracted content.
Parameters:
query(str): Search query or keywords to find relevant web content
Returns:
List of results, each containing:
url(str): The webpage URLcontent(str): Page content in Markdown format
web_fetch
Fetches content from a specified URL and converts it to Markdown.
Parameters:
url(str): The URL to fetch content from
Returns:
String containing the page content in Markdown format
youtube_get_subtitles
Gets subtitles/captions from a YouTube video and returns the text content.
Parameters:
url(str): YouTube video URL to get subtitles from
Returns:
String containing the subtitles with timestamps in format: [HH:MM:SS] text
How Search Works
SSMCP uses a pipeline to deliver clean content from web searches:
1. Search (SearXNG)
Queries are sent to a local SearXNG instance
SearXNG aggregates results from multiple search engines
Returns a list of URLs with titles and snippets
2. Content Extraction (Crawl4AI)
Each URL is fetched using headless Chromium browser
Pages are fully rendered (JavaScript executed, dynamic content loaded)
Raw content is extracted
All URLs are processed concurrently
3. Content Filtering
Two-stage filtering extracts clean main content:
CSS Selector Filter - Tries selectors (
article,main, etc.) to find main content areaResidual Junk Filter - Removes UI artifacts (tooltips, duplicate text)
If any filter produces output, the filtered HTML is re-processed through Crawl4AI for cleaner output before markdown conversion.
4. Markdown Conversion
Converts filtered HTML to clean Markdown
Removes images and external links
5. Optional: LLM Summarization
When enabled, SSMCP uses an LLM to summarize search results before returning them to your AI model. This reduces the token count in your context window - search results can be 40k-60k tokens, but summaries significantly reduce that.
Note: LLM summarization is disabled by default. Enable it via environment variables if needed (see .env.example).
Development
All development tasks are performed inside the Docker container. Nothing needs to be installed on the host machine except Docker and Docker Compose.
Available Make Commands
Run make help to see all available commands:
Enable Development mode:
Open.envand uncomment the lineCOMPOSE_FILE=docker-compose.yml:docker-compose.dev.ymlStart the services:
make buildOpen a shell in the container:
make shellInside the shell, you can run any command:
uv run python -m ssmcp.server uv run pytest -vEdit code on your host machine - Changes are automatically reflected in the container via volume mounts
Run tests:
make testCheck code quality (lint + type-check):
make checkRestart or rebuild if needed:
make restart make rebuildStop services:
make down
Configuration
All configuration is managed through environment variables. See .env.example for available options
OpenWebUI OAuth Authentication
SSMCP supports OAuth authentication for use with OpenWebUI and any OIDC-compliant identity provider.
How OpenWebUI OAuth Works
When you select OAuth in OpenWebUI for an MCP server:
OpenWebUI forwards the system user's OAuth access token in the
Authorization: Bearer <token>headerThe token is a JWT containing user information from the identity provider
SSMCP validates the token and extracts the user identifier from the
subclaim
To enable OAuth authentication, set the following environment variables in your .env file:
# Enable OAuth authentication
OAUTH_ENABLED=true
# JWKS endpoint URL for your identity provider's public keys
# Examples:
# Authentik: https://authentik.example.com/application/o/my-app/jwks
OAUTH_JWKS_URL=https://your-idp.example.com/path/to/jwks
# Issuer URL for token issuer verification
# Must match the 'iss' claim in JWT tokens
# Examples
# Authentik: https://authentik.example.com/application/o/my-app
OAUTH_ISSUER=https://your-idp.example.com/application/o/my-app
# Open WebUI client ID for token audience verification
OAUTH_CLIENT_ID=your-openwebui-client-idWhen OAuth is enabled, SSMCP validates:
JWT Signature: Verifies the token signature using the identity provider's public keys from the JWKS endpoint
Issuer: Validates the
issclaim matchesOAUTH_ISSUERExpiration: Validates the
expclaim - rejects expired tokensAudience: Validates the
audclaim matchesOAUTH_CLIENT_IDSubject: Requires the
subclaim (contains user identifier)
In OpenWebUI, configure the MCP server with:
Type: MCP Streamable HTTP
URL: Your SSMCP server URL (e.g.,
http://ssmcp:8000/mcp)Auth: OAuth
The system will automatically forward the user's OAuth token
SSMCP works with any OIDC-compliant identity provider that:
Provides a JWKS endpoint for public key distribution
Issues JWT access tokens with RS256 signing
Includes standard claims (
sub,aud,exp,iss)
License
Apache License 2.0 - see LICENSE file for details.
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Maintenance
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