MCP Server Suite
This suite provides five production-ready MCP servers for restaurant orders, web search, browser automation, and filesystem operations, supporting both stdio and HTTP/SSE transports.
README
MCP Server Suite
Five production-ready Model Context Protocol (MCP) servers built with the official Python SDK. Supports both stdio and HTTP/SSE transports.
This suite enables any MCP-compatible client (Claude Desktop, Cursor, OpenCode) to interact with restaurant data, web search, browser automation, and filesystem operations.
What is MCP?
MCP is an open standard that lets AI applications connect to external tools and data sources through a uniform interface. Think of it as USB-C for AI tools — write once, integrate everywhere.
Servers
1. restaurant_server (stdio)
Wraps restaurant ordering tools for MCP clients.
Tools: get_menu, check_dish_availability, check_quantity, add_item_to_cart, view_cart, get_suggestions, finalize_order
2. searxng_server (stdio)
Wraps a local SearXNG meta-search engine.
Tools: web_search, image_search
- Supports categories, language, safesearch, time range, and result count
- Uses
httpx.AsyncClientfor non-blocking requests
3. pinchtab_server (stdio)
Wraps a local PinchTab headless browser.
Tools: navigate, snapshot, click, fill, extract_text
- Enables LLM-driven web browsing and form interaction
- Communicates via PinchTab's REST API
4. filesystem_server (stdio)
Sandboxed filesystem operations with path traversal protection.
Tools: read_file, write_file, list_directory, search_files, file_stat, move_file, copy_file, delete_file
_resolve()enforces workspace sandboxing viaPath.relative_to()- Binary files returned as base64
5. filesystem_server_sse (HTTP/SSE)
The same filesystem server exposed over Server-Sent Events on HTTP.
- Built with Starlette + uvicorn + anyio memory streams
- Per-session JSON-RPC message routing
- Endpoints:
/(info),/sse(event stream),/messages(POST)
Quick Start
1. Install
pip install -r requirements.txt
2. Configure MCP Client
Copy mcp.json.example to your client's config directory and update URLs:
cp mcp.json.example ~/.config/claude/mcp.json # Claude Desktop
cp mcp.json.example ~/.config/opencode/mcp.json # OpenCode
3. Run Individual Servers
# stdio servers (spawned by MCP client)
python -m mcp_servers.restaurant_server
python -m mcp_servers.searxng_server
python -m mcp_servers.pinchtab_server
python -m mcp_servers.filesystem_server /path/to/workspace
# SSE server (runs as HTTP daemon)
python -m mcp_servers.filesystem_server_sse /path/to/workspace
# Then connect to http://localhost:3000/sse
SSE Transport Deep Dive
The SSE server is the most technically interesting component:
# Per-session memory streams
rx_send, rx_recv = anyio.create_memory_object_stream(100)
tx_send, tx_recv = anyio.create_memory_object_stream(100)
# MCP server runs in background asyncio task
await server.run(rx_recv, tx_send, server.create_initialization_options())
# SSE handler serializes messages as JSON events
yield f"event: message\ndata: {message.model_dump_json()}\n\n"
# Client POSTs to /messages, injected into receive stream
await SESSIONS[session_id]["rx_send"].send(JSONRPCMessage.model_validate(data))
Key design decisions:
- Memory streams decouple HTTP I/O from MCP protocol logic
- Session cleanup on disconnect prevents resource leaks
- JSON-RPC message validation ensures protocol compliance
Environment Variables
| Variable | Default | Description |
|---|---|---|
SEARXNG_URL |
http://localhost:8080 |
SearXNG base URL |
PINCHTAB_URL |
http://localhost:9867 |
PinchTab API URL |
RESEARCH_WORKSPACE |
~/workspace/research |
Research report output directory |
MCP_HOST |
0.0.0.0 |
SSE server bind host |
MCP_PORT |
3000 |
SSE server bind port |
Architecture
MCP Client (Claude Desktop / Cursor / OpenCode)
|
v
+-- stdio transport --+ +-- SSE transport --+
| python -m server | | http://host:3000 |
+--------------------+ +-------------------+
| |
v v
Restaurant Data Filesystem Ops
SearXNG Search (remote access)
PinchTab Browser
Security Notes
- Filesystem sandboxing:
_resolve()prevents path traversal above workspace root - stdio transport: No open network ports — most secure option
- SSE transport: Bind to
127.0.0.1or use reverse proxy with TLS for remote access - PinchTab IDPI: Restricts browsing to allowed origins by default
Testing
Each server can be tested manually:
# Test SearXNG MCP server
python -m mcp_servers.searxng_server
# Then send JSON-RPC messages via stdin
# Test filesystem SSE server
curl http://localhost:3000/
curl http://localhost:3000/sse
Tech Stack
| Component | Technology |
|---|---|
| MCP Framework | mcp Python SDK |
| HTTP Client | httpx (async) |
| SSE Server | starlette + uvicorn + anyio |
| Data Format | JSON / JSON-RPC |
License
MIT
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.