zosmaai/pi-llm-wiki

Self-maintaining, Obsidian-compatible knowledge base for pi — turn raw sources into an interlinked wiki that compounds. Native Open Knowledge Format (OKF) v0.2.

What it solves

One-shot RAG (Retrieval-Augmented Generation) often results in ephemeral synthesis where the model searches raw documents but fails to retain insights over time. pi-llm-wiki creates a durable, interlinked knowledge base that compounds as you capture sources and perform analyses, transforming raw data into a structured wiki that persists across sessions.

How it works

The system uses a layered vault architecture (Personal and Project levels) to store knowledge in an Obsidian-compatible format. It processes information through a four-layer pipeline:

  1. Raw Source Packets: Immutable captures of URLs, PDFs, and other files.
  2. Source Pages: Summaries of what each specific source contains.
  3. Canonical Wiki Pages: High-level tracking of concepts, entities, and syntheses.
  4. Generated Metadata: Searchable registries and backlinks that keep the wiki navigable.

It integrates as an extension for the pi and oh-my-pi agents and also provides a standalone MCP (Model Context Protocol) server for use with clients like Claude Code, Cursor, and Windsurf.

Who it’s for

Developers and researchers who want a self-maintaining knowledge base that evolves with their projects, and those using AI agents that need a persistent, structured "working memory" for complex tasks.

Highlights

  • Layered Recall: Simultaneously searches both a global personal vault (~/.llm-wiki/) and a project-specific vault.
  • Open Knowledge Format (OKF) v0.2: Uses a portable, non-proprietary format to avoid vendor lock-in.
  • Agent Working-Memory: Optional capability to record tool-call trajectories and distill them into reusable skill pages.
  • Obsidian Compatibility: Knowledge is stored as Markdown with wikilinks, making it viewable in Obsidian.
  • Automated Ingestion: Batch-processes raw sources into structured concept and analysis pages via wiki_ingest.
  • MCP Server: Exposes wiki tools to any MCP-compatible AI client via stdio transport.

Related

  • Project
    xoai/sage-wiki

    A graph-based knowledge base that uses an LLM compiler to turn raw documents into an interlinked wiki and knowledge graph for AI agents and humans.

  • Project
    VectifyAI/OpenKB

    An open-source system that compiles raw documents into a structured, interlinked wiki-style knowledge base using LLMs and vectorless, reasoning-based retrieval.

  • Project
    Ar9av/obsidian-wiki

    A tool that allows AI agents to build and maintain a persistent, interconnected markdown knowledge base for the user, preventing knowledge loss from chat logs.

  • Project
    nashsu/llm_wiki

    LLM Wiki is a desktop app that automatically ingests documents, uses a two‑step LLM chain‑of‑thought to create a structured, Obsidian‑compatible markdown wiki, and provides hybrid keyword/vector/graph search, a Rust‑backed chat agent, knowledge‑graph visualisation with community detection, and deep‑research web‑search integration.

  • Project
    nvk/llm-wiki

    llm‑wiki is a cross‑runtime tool that lets Claude, Codex, OpenCode, Pi and other LLM agents build and query a structured, Obsidian‑compatible wiki. It provides ingestion, parallel research, session memory, private adapters, and exportable knowledge checkpoints, with install scripts for each supported agent.