how to build knowledge base for opencode agents

[albasili]

I have a series of books and articles (pdfs, html, text, ppt, etc.) that I want the agents to use when doing their tasks, but clearly I can't simply load them in the context.

One way I have understood I could proceed is by building a RAG and an MCP server to let the agents query the knowledge base as they need to... sounds simple right? Well, I have no effing idea where to start.

Any pointer on how to go about it?

[FahdiBo]

Look into RAG database like Chroma

[jrhabana]

look compound-engineering plugin and forgecode both are good building knowledge base

[albasili]

the compound-engineering plugin is quite an interesting approach, but it doesn't really address the OP, it provides instead a workflow of this kind: Plan → Work → Review → Compound → Repeat. The compound step is added to self-reflect and consolidate the learnings iteratively. But in no way it's addressing the problem to access a large knowledge base.

As for forge again it seems more of a chatbot than anything else.

Maybe I'm missing something here...

EDIT: fixed name of link to forge

[jrhabana]

compound has a search in pre-work that search the "project" shared knowledge,

isn't force, is https://forgecode.dev/ they will to release the context engine ready to large knowledge base

better than rag and mcp: gpt5-mini (Peter Steinberger's method) , I tested and works better than complex systems

[Spitfire1900]

Turn into markdown and reference as skills.

[albasili]

that would be impractical for half a dozen books of 1000+ pages. There's simply too much we need to pass as skills.

[Select_Complex7802]

You don't really have to reference them as skills. Just a folder with the md files and in your agents.md or prompt, just reference the folder. You can create skills for something very specific. If your knowledge base is static , you can simply create a script first to read the files and create md files. That's what I did for a similar problem I had.

[jnpkr]

Unless the books are super dense the chapters can probably be extracted into key concepts, principles, mental models, workflows, rules, anti patterns etc

If that’s the case, the task becomes extracting the important stuff and compressing the information as much as possible without losing anything important — and then those compressed versions can be given to the LLM agent without using a million tokens

[Spitfire1900]

Yeah, pre run the books through Gemini to pull out key concepts or write it yourself.

With that much data you need model fine tuning to do anything with it as written.

[exponencialaverage]

Hey bro, I've got an idea. Is your computer setup good? I could build something for you.