MCP Server for Apache Jena

by ramuzes
Verified

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Integrations

  • Manages environment variables for configuring the MCP server, including API keys, server URLs, and dataset specifications.

  • Connects to Apache Jena Fuseki server to execute SPARQL queries and updates against RDF data, allowing access to and modification of graph databases.

  • Hosts the repository for the MCP server code, allowing for version control and distribution of the server implementation.

MCP Server for Apache Jena

A Model Context Protocol (MCP) server that connects AI agents to Apache Jena for SPARQL query capabilities.

Overview

This project implements an MCP server that allows AI agents (such as Cursor, Claude for Cline, or Claude Desktop) to access and query RDF data stored in Apache Jena. The server provides tools for executing SPARQL queries and updates against a Jena Fuseki server.

Features

  • Execute SPARQL queries against a Jena Fuseki server
  • Execute SPARQL updates to modify RDF data
  • List available named graphs in the dataset
  • HTTP Basic authentication support for Jena Fuseki
  • Compatible with the Model Context Protocol

Prerequisites

  • Node.js (v16 or later)
  • Apache Jena Fuseki server running with your RDF data loaded
  • An AI agent that supports the Model Context Protocol (e.g., Cursor, Claude for Cline)

Installation

  1. Clone this repository:
    git clone https://github.com/ramuzes/mcp-jena.git cd mcp-jena
  2. Install dependencies:
    npm install
  3. Build the TypeScript code:
    npm run build

Usage

Run the server with default settings (localhost:3030 for Jena, 'ds' for dataset):

npm start

Or specify custom Jena endpoint, dataset, and authentication credentials:

npm start -- --endpoint http://your-jena-server:3030 --dataset your_dataset --username your_username --password your_password

You can also use short flags:

npm start -- -e http://your-jena-server:3030 -d your_dataset -u your_username -p your_password

For development mode with automatic transpilation:

npm run dev:transpile -- -e http://your-jena-server:3030 -d your_dataset -u your_username -p your_password

Available Tools

This MCP server provides the following tools:

  1. execute_sparql_query - Execute a SPARQL query against the Jena dataset
  2. execute_sparql_update - Execute a SPARQL update query to modify the dataset
  3. list_graphs - List all available named graphs in the dataset

Environment Variables

You can also configure the server using environment variables:

  • JENA_FUSEKI_URL: URL of your Jena Fuseki server (default: http://localhost:3030)
  • DEFAULT_DATASET: Default dataset name (default: ds)
  • JENA_USERNAME: Username for HTTP Basic authentication to Jena Fuseki
  • JENA_PASSWORD: Password for HTTP Basic authentication to Jena Fuseki
  • PORT: Port for the MCP server (for HTTP transport, default: 8080)
  • API_KEY: API key for MCP server authentication

Example SPARQL Queries

Basic SELECT query:

SELECT ?subject ?predicate ?object WHERE { ?subject ?predicate ?object } LIMIT 10

Insert data with UPDATE:

PREFIX ex: <http://example.org/> INSERT DATA { ex:subject1 ex:predicate1 "object1" . ex:subject2 ex:predicate2 42 . }

Query a specific named graph:

SELECT ?subject ?predicate ?object FROM NAMED <http://example.org/graph1> WHERE { GRAPH <http://example.org/graph1> { ?subject ?predicate ?object } } LIMIT 10

Resources

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security - not tested
F
license - not found
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quality - not tested

A Model Context Protocol server that connects AI agents to Apache Jena, enabling them to execute SPARQL queries and updates against RDF data stored in Jena Fuseki.

  1. Overview
    1. Features
      1. Prerequisites
        1. Installation
          1. Usage
            1. Available Tools
              1. Environment Variables
                1. Example SPARQL Queries
                  1. Basic SELECT query:
                  2. Insert data with UPDATE:
                  3. Query a specific named graph:
                2. Resources
                  ID: xk4oivwafn