agent-wiki

The knowledge base that makes AI agents smarter over time.

Instead of retrieving raw fragments every query (RAG), your agent compiles, refines, and interlinks knowledge — like a team wiki that writes itself.

Works with Claude Code, Cursor, Windsurf, and any MCP client. No LLM built in — your agent IS the intelligence.

Quick Start

npx @agent-wiki/mcp-server serve --wiki-path ./my-knowledge

Add to your MCP client config (Claude Code, Cursor, Windsurf, Claude Desktop):

{
  "mcpServers": {
    "agent-wiki": {
      "command": "npx",
      "args": ["-y", "@agent-wiki/mcp-server", "serve", "--wiki-path", "/path/to/knowledge"]
    }
  }
}

That's it. Your agent now has a persistent, structured knowledge base.

Why Not RAG?

| | RAG | agent-wiki | |---|---|---| | Approach | Retrieve fragments at query time | Build and maintain compiled knowledge | | Memory | Stateless — forgets after each query | Persistent — knowledge accumulates | | Quality | Raw chunks, often noisy | Curated, structured, interlinked | | Cost | Embedding + retrieval every query | One-time compilation, free reads | | Contradictions | Invisible — buried in source docs | Flagged automatically by lint | | Source tracking | Lost after retrieval | Full provenance chain (raw -> wiki) |

Features

| Feature | Description | |---------|-------------| | Immutable Sources | SHA-256 verified raw/ layer — write-once, tamper-proof, full provenance | | Knowledge Compilation | Agent builds structured wiki pages from raw sources — not retrieve-and-forget | | BM25 Search | Field-weighted scoring, synonym expansion, fuzzy matching, CJK tokenization — zero LLM | | Auto-Classification | Zero-LLM heuristic assigns entity types and tags across 10 categories | | Multi-Level Indexes | Auto-generated index.md at every directory level — nested topic hierarchies with sub-topic navigation | | Self-Checking Lint | Catches contradictions, broken links, orphan pages, stale content | | Atlassian Import | One-command Confluence pages and Jira issues with full hierarchy | | File Versioning | Auto-version same-name files, query latest, list all versions | | Directory Import | Point to a folder — imports all files with optional glob filtering | | Document Extraction | PDF (with per-page access), DOCX, XLSX (multi-tab), PPTX — text extracted automatically | | 16 MCP Tools | Full CRUD + search + lint + health checks | | Git-Native | Plain Markdown — diffable, blameable, revertable |

Architecture

Three immutability layers, inspired by how compilers work:

| Layer | Mutability | Role | |-------|-----------|------| | raw/ | Immutable | Source documents — write-once, SHA-256 verified | | wiki/ | Mutable | Compiled knowledge — structured pages that improve over time | | schemas/ | Reference | Entity templates — consistent structure across knowledge types |

Design Principles

1. Raw is immutable — Source documents are write-once, SHA-256 verified. Ground truth never changes.
2. Wiki is mutable — Compiled knowledge improves with every interaction.
3. No LLM dependency — Zero API keys, zero cost per operation. Your agent IS the intelligence.
4. Self-checking — Lint catches structural issues and flags potential contradictions.
5. Knowledge compounds — Every write enriches the whole wiki. Synthesis creates higher-order understanding.
6. Provenance matters — Every wiki claim traces back to raw sources.
7. Git-native — Plain Markdown. Every change is diffable, blameable, and revertable.

Documentation

• MCP Tools (16) & Entity Types
• Configuration, CLI & Security

Acknowledgment

Inspired by Andrej Karpathy's LLM Wiki concept — the idea that AI agents should compile and maintain knowledge, not just retrieve raw fragments. This project is an independent, full implementation of that vision.

License

MIT