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Yet Sparql Mcp Server

Created By
Temkit Sid-Ali10 months ago
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-agnostic interface for querying semantic data.
Overview

What is Yet Sparql Mcp Server?

Yet Sparql Mcp Server is a high-performance, configurable server that connects to any SPARQL endpoint, providing enhanced functionality such as result formatting and caching. It is built on the MCP (Message Carrying Protocol) framework, offering a seamless, language-agnostic interface for querying semantic data.

How to use Yet Sparql Mcp Server?

To use the server, start it by specifying a SPARQL endpoint using the command: mcp-server-sparql --endpoint https://dbpedia.org/sparql. You can also run it as a background daemon or configure it with systemd for automatic startup.

Key features of Yet Sparql Mcp Server?

  • Universal endpoint support for any SPARQL-compliant endpoint.
  • Full SPARQL support for executing any valid SPARQL query (SELECT, ASK, CONSTRUCT, DESCRIBE).
  • Intelligent result formatting options: standard JSON, simplified JSON, and tabular format.
  • High-performance caching with multiple strategies (LRU, LFU, FIFO) and configurable TTL.
  • Flexible deployment options including foreground mode, background daemon, and systemd service.

Use cases of Yet Sparql Mcp Server?

  1. Querying semantic data from various SPARQL endpoints.
  2. Formatting results for different application needs (e.g., UI display).
  3. Caching results to improve performance and reduce load on SPARQL endpoints.

FAQ from Yet Sparql Mcp Server?

  • Can I connect to any SPARQL endpoint?
    Yes, the server supports any SPARQL-compliant endpoint.

  • What formats can I get results in?
    You can receive results in standard JSON, simplified JSON, or tabular format.

  • Is caching enabled by default?
    Yes, caching is enabled by default, and you can configure its behavior.

Server Config

{
  "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"
}
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