OriginTrail DKG MCP Server Overview

The OriginTrail Decentralized Knowledge Graph (DKG) MCP Server bridges AI assistants with a distributed, verifiable knowledge base. By exposing a set of MCP‑compatible tools, the server lets agents query, create, and manage data on the DKG without needing to understand the underlying blockchain or graph protocols. This removes a significant friction point for developers who want their assistants to work with immutable, trust‑worthy facts.

At its core, the server offers SPARQL querying and knowledge asset creation. Agents can issue flexible SPARQL queries to pull structured information from the DKG, or they can provide natural‑language descriptions that the server converts into schema.org‑compliant JSON‑LD before publishing it to the graph. Both operations are wrapped as MCP tools, making them callable from any LLM or agent framework that supports the protocol. The server also manages agent memory in a decentralized manner, allowing assistants to store and retrieve context directly on the DKG rather than relying on local or cloud‑based state.

Key capabilities include:

• Decentralized persistence – All knowledge assets are anchored on a blockchain, guaranteeing tamper‑evidence and provenance.
• Interoperability – The server speaks MCP, so any client—VS Code extensions, Cursor, Claude, or Microsoft Copilot Studio agents—can immediately tap into the DKG.
• Extensibility – Developers can add new tools or modify existing ones through simple Python functions decorated with . Prompt templates in the folder let you fine‑tune LLM behavior for specific use cases.
• Dual transport modes – Run locally via stdio for quick prototyping, or deploy as an SSE endpoint to expose the DKG MCP server to cloud‑based agents.

Typical use cases span several domains. In supply‑chain traceability, an AI assistant can query the DKG to verify product provenance or add new shipment records. In compliance, agents can pull regulatory data and publish audit logs directly to the graph. Educational bots might use the server to fetch up‑to‑date facts and store student interactions as verifiable learning artifacts. Because the server handles all graph interactions, developers can focus on higher‑level logic while ensuring that every piece of data remains immutable and auditable.

By integrating the OriginTrail DKG MCP Server into AI workflows, teams gain a powerful, blockchain‑backed knowledge layer that enhances transparency, reduces data silos, and enables new types of verifiable AI services.