Build a local AI setup and personal knowledge graph

They had Hermes Agent assemble a local AI stack and connect Gbrain for chat-based knowledge-graph lookups.

Done with Hermes Agent· Advanced

What they did
Ivan Fioravanti used Hermes Agent to talk through a local AI lab build that brought together liteLLM, Postgres, Prometheus, and Grafana. In a separate example, Alvaro Cintas had it add Gbrain, an open-source tool from Garry Tan, as an MCP server and use it for entity-aware recall.
How it went
Both examples were described as functioning demos. The write-up says Gbrain’s benchmark came out 31 points ahead of plain vector search. It does not mention how long either setup took, what they cost, or any problems along the way.
Tips
A large context window matters here: Hermes needs at least 64K tokens. If you try this yourself, have the agent confirm each change and stop before anything that could replace or erase data.

Try it yourself with Hermes Agent

Help me create a local AI environment on [machine/system] with [liteLLM, Postgres, Prometheus, Grafana, or other components I choose]. After that, add [Gbrain or a different MCP server for knowledge graphs] so I can query [my notes/documents/files] through a personal knowledge graph. For every step, tell me what you plan to do and wait for my approval before proceeding. Pause and ask me first before any action that might overwrite, remove, send, or submit something. When you are done, confirm that each service is up and give me one test query I can run.

Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.

Read the original on kie.ai ↗

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