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OriginTrail DKG MCP Server (example)

@OriginTrail

Repository

Basic information

Category

Other

Transports

stdio

Author

OriginTrail

About OriginTrail DKG MCP Server

Example python MCP server for DKG nodes

#dkg#mcp#server#origintrail

OriginTrail DKG MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "dkg-mcp-server": {
      "command": "python",
      "args": [
        "dkg_server.py",
        "--transport",
        "stdio"
      ]
    }
  }
}

OriginTrail DKG MCP Server tools

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.

Overview

What is OriginTrail DKG MCP Server (example)?

The OriginTrail DKG MCP Server connects MCP-compatible agents with the OriginTrail Decentralized Knowledge Graph (DKG), enabling the creation, retrieval, linking, and exchange of verifiable knowledge. It is beta software and not recommended for production use.

How to use OriginTrail DKG MCP Server (example)?

Clone the repository, install dependencies with Python 3.10+ and pip install -r requirements.txt, configure environment variables (ORIGINTRAIL_NODE_URL, BLOCKCHAIN, PRIVATE_KEY, GOOGLE_API_KEY), then run python dkg_server.py --transport stdio for local clients or python dkg_server.py --transport sse for server deployment. The server exposes tools such as query_dkg_by_name and create_knowledge_asset via MCP.

Key features of OriginTrail DKG MCP Server (example)

  • SPARQL querying of the Decentralized Knowledge Graph.
  • Natural language to structured JSON-LD knowledge asset creation.
  • Decentralized, interoperable agent memory storage.
  • Works with any MCP-compatible client or agentic framework.
  • Supports both stdio and SSE transport modes.

Use cases of OriginTrail DKG MCP Server (example)

  • Enabling AI agents to query and retrieve verifiable knowledge from the DKG.
  • Publishing structured, schema.org-compliant knowledge assets from natural language.
  • Storing and sharing interoperable agent memory across different MCP clients.
  • Integrating DKG capabilities into VS Code, Cursor, Claude, or Microsoft Copilot Studio agents.

Frequently asked questions

1

Is this server ready for production?

No, it is beta software and not recommended for production use.

2

What are the runtime requirements?

Python 3.10+ and environment variables for ORIGINTRAIL_NODE_URL, BLOCKCHAIN, PRIVATE_KEY, and GOOGLE_API_KEY.

3

What transport modes are supported?

Stdio mode for local clients (VS Code, Cursor, Claude) and SSE mode for server deployment (e.g., Microsoft Copilot Studio agents).

4

How can I extend the server with new tools?

Define new functions in `dkg_server.py` using the `@mcp.tool()` decorator. Custom prompts can be added in the `prompts/` directory.

5

Which clients are compatible with this server?

Any MCP-compatible client, including VS Code, Cursor, Claude, Microsoft Copilot Studio agents, and other agentic frameworks.

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