Stop stuffing entire 5,000-line files into your AI context window.
OMNIA parses your repository into an AST symbol graph, serving surgical caller/callee slices to AI coding agents in <16ms.
⚡ 10-Second Claude Setup • 📊 Token Compression Benchmarks • 🛠️ Available MCP Tools
Add to your claude_desktop_config.json:
{
"mcpServers": {
"omnia-memory": {
"command": "python",
"args": ["-m", "core.omnia_server", "--workspace", "C:/path/to/repo"]
}
}
}| Query Type | Traditional Full File Read | OMNIA AST Symbol Retrieval | Token Reduction |
|---|---|---|---|
| Single Function Call | 2,840 tokens | 148 tokens | -94.8% |
| Class Interface Audit | 8,200 tokens | 612 tokens | -92.5% |
| Dependency Flow Trace | 14,500 tokens | 890 tokens | -93.8% |
- Deterministic Symbol Map: Fast AST indexing across Python, TypeScript, C++, and Go.
- Caller/Callee Dependency Graphs: Instant resolution of upstream and downstream references.
- Relational Memory Storage: High-performance SQLite WAL backend with zero external database dependencies.