What are the system requirements?
Python 3.8 or newer is required, along with the `SPARQLWrapper`, `mcp`, `pydantic`, and `python-daemon` libraries.
@yet-market
Basic information
MCP SPARQL Server is a high-performance, configurable server that connects to any SPARQL endpoint and provides enhanced functionality including result formatting and caching. It's built on top of the MCP (Message Carrying Protocol) framework to provide a seamless, language-agnost
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": [
{
"name": "sparql",
"command": "python3",
"args": [
"/path/to/server.py",
"--endpoint",
"https://data.legilux.public.lu/sparqlendpoint",
"--format",
"simplified",
"--cache-enabled",
"true",
"--cache-ttl",
"300",
"--cache-strategy",
"lru"
],
"env": {
"SPARQL_ENDPOINT": "https://data.legilux.public.lu/sparqlendpoint",
"SPARQL_TIMEOUT": "30",
"SPARQL_MAX_RESULTS": "1000",
"SPARQL_CACHE_ENABLED": "true",
"SPARQL_CACHE_TTL": "300",
"SPARQL_CACHE_MAX_SIZE": "100",
"SPARQL_CACHE_STRATEGY": "lru",
"PYTHONPATH": "/path/to/project/directory"
},
"transport": "stdio"
}
],
"defaultServer": "sparql"
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Yet Sparql Mcp Server is a configurable server that connects to any SPARQL endpoint and provides result formatting and caching. It is built on the Message Carrying Protocol (MCP) framework to offer a language-agnostic interface for querying semantic data.
Install via pip install mcp-server-sparql or from source. Start the server by specifying a SPARQL endpoint: mcp-server-sparql --endpoint URL. Queries are sent using the MCP client with JSON actions that include a query_string and optional format parameter. The server can run in foreground mode, as a background daemon, or as a systemd service.
Python 3.8 or newer is required, along with the `SPARQLWrapper`, `mcp`, `pydantic`, and `python-daemon` libraries.
Yes, the server is designed to work with any SPARQL-compliant endpoint by specifying its URL via `--endpoint` or the `SPARQL_ENDPOINT` environment variable.
Three formats are available: standard JSON (default), simplified JSON (key-value pairs), and tabular (columns and rows). You can set the format at startup with `--format` or per query with the `format` parameter.
The server supports three cache replacement strategies: LRU (least recently used, default), LFU (least frequently used), and FIFO (first in first out). You can configure cache TTL, maximum size, and enable/disable caching via command‑line arguments or environment variables.
Yes, use `--daemon` to run as a background process, and optionally set up a systemd service using the provided installation script. Logs and PID files are configurable.

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