your-repo/
    src/auth/middleware.py   →  AI summary + import graph
    src/db/pool.py           →  AI summary + import graph
    ...
           ↓  codelore ingest
your-repo_vault/
    INDEX.md                 overview + wikilinks to all modules
    src/auth/middleware.md   structured summary of every function
    src/db/pool.md           ...
your-repo_chroma/            ChromaDB: chunks indexed by developer questions

pip install codelore

git clone https://github.com/yourname/codelore
pip install -e codelore

# 1. Ingest a local repo (or pass a GitHub URL)
codelore ingest /path/to/your-repo

# Preview cost before running on a large repo
codelore ingest /path/to/your-repo --dry-run

# Re-use cached summaries from a previous run (skips claude calls)
codelore ingest /path/to/your-repo   # prompted automatically if cache exists

# 2. Query from the terminal
codelore query "how does authentication work?" \
  --chroma /path/to/your-repo_chroma

# 3. Print MCP setup instructions
codelore init --vault /path/to/your-repo_vault \
              --chroma /path/to/your-repo_chroma \
              --repo /path/to/your-repo

{
  "mcpServers": {
    "codelore": {
      "command": "codelore-mcp",
      "env": {
        "CODELORE_VAULT_ROOT": "/path/to/your-repo_vault",
        "CODELORE_CHROMA_PATH": "/path/to/your-repo_chroma",
        "CODELORE_REPO_ROOT": "/path/to/your-repo"
      }
    }
  }
}

# via MCP tool (in Claude Code):
"sync the vault for /path/to/repo"   →  calls sync_vault(dry_run=True) first

# or directly:
sync_vault(repo_path="/path/to/repo", explanations_json_path="..._explanations.json", dry_run=True)
sync_vault(repo_path="/path/to/repo", explanations_json_path="..._explanations.json", dry_run=False)

codelore/
  main.py          CLI entry point (ingest / query / init subcommands)
  ingest.py        build file/directory graph, write vault markdown
  explain.py       collect files, call Claude CLI for summaries
  llm.py           Claude CLI wrapper, prompt templates
  nodes.py         FileNode / DirectoryNode / IndexNode → markdown
  generate_questions.py  chunk-level question generation + ChromaDB indexing
  parsers/         language-specific import graph + chunk extraction
    _treesitter.py shared tree-sitter helper
    python.py      stdlib ast
    javascript.py  tree-sitter-javascript / tree-sitter-typescript
    go.py          tree-sitter-go
    jvm.py         tree-sitter-java / tree-sitter-kotlin / tree-sitter-scala
    csharp.py      tree-sitter-c-sharp
    haskell.py     tree-sitter-haskell
    elixir.py      tree-sitter-elixir
    lua.py         tree-sitter-lua
    shell.py       tree-sitter-bash
    ...
  query/
    retrieval.py   search_chunks, bfs_vault, grep_todos, git_file_log
mcp_server.py      FastMCP server exposing 9 tools