A Model Context Protocol (MCP) server that provides conversational interface for the exploration and analysis of RDF (Turtle) based Knowledge Graph
A Model Context Protocol (MCP) server that provides conversational interface for the exploration and analysis of RDF (Turtle) based Knowledge Graph in Local File mode or SPARQL Endpoint mode. That is what the rdf explorer v1.0.0 mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
The server exposes the following resources: - schema://all: Retrieve schema information (classes and properties) from the graph. - Returns: A newline-separated string of schema elements (classes and properties).
The server publishes 12 tools. What each one is for:
execute_on_endpoint — Execute a SPARQL query directly on an external endpointInput — - endpoint (str): The SPARQL endpoint URL to queryReturns — Query results as a newline-separated string, or an error messagesparql_query — Execute a SPARQL query on the current graph or active external endpointgraph_stats — Calculate and return statistics about the graph in JSON formatcount_triples — Count triples in the graph. Disabled in SPARQL Endpoint Mode; use a custom prompt insteadfull_text_search — Perform a full-text search on the graph or endpoint, avoiding proprietary syntaxhealth_check — Check the health of the triplestore connectionget_mode — Get the current mode of RDF Explorer. Useful for knowledge graph and semantic tech users to verify data sourceTools — The server implements SPARQL queries and search functionality:Resources — The server exposes the following resources: - schema://all: Retrieve schema information (classes and properties) from the graph. - Returns: APrompts — The server exposes the following prompts: - analyze_graph_structure: Initiate an analysis of the graph structure with schema data. - Returns: A listSetup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Plenty of knowledge and memory servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. RDF Explorer V1.0.0's toolset — execute_on_endpoint, Input, Returns and 9 more — is a fair guide to whether it matches your workflow. It is maintained by emekaokoye; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| execute_on_endpoint | Execute a SPARQL query directly on an external endpoint |
| Input | - endpoint (str): The SPARQL endpoint URL to query. |
| Returns | Query results as a newline-separated string, or an error message. |
| sparql_query | Execute a SPARQL query on the current graph or active external endpoint |
| graph_stats | Calculate and return statistics about the graph in JSON format |
| count_triples | Count triples in the graph. Disabled in SPARQL Endpoint Mode; use a custom prompt instead. |
| full_text_search | Perform a full-text search on the graph or endpoint, avoiding proprietary syntax. |
| health_check | Check the health of the triplestore connection. |
| get_mode | Get the current mode of RDF Explorer. Useful for knowledge graph and semantic tech users to verify data source. |
| Tools | The server implements SPARQL queries and search functionality: |
| Resources | The server exposes the following resources: - schema://all: Retrieve schema information (classes and properties) from the graph. - Returns: A newline-separated string of schema elements (classes and properties). |
| Prompts | The server exposes the following prompts: - analyze_graph_structure: Initiate an analysis of the graph structure with schema data. - Returns: A list of messages to guide graph structure analysis. |
{
"mcpServers": {
"rdf_explorer": {
"command": "C:\\path\\to\\venv\\Scripts\\python.exe",
"args": ["C:\\path\\to\\server.py", "--triple-file", "your_file.ttl"]
}
}
}Configuration as documented by the project. Restart the client after saving.
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