Code Intelligence
Pre-built maps of your codebase — graphs, indexes and architecture views agents query instead of grepping.

Agent skill for architecture, workflow, sequence, data-flow and lifecycle diagrams: the agent emits typed JSON IR, Archify compiles it deterministically to interactive HTML/SVG with PNG/WebM export.
AST-based semantic code search for coding agents: pipx install, zero config, local embeddings out of the box — a CLI/skill/MCP that cuts agent context ~70% vs grepping. Built on CocoIndex.

Parses a polyglot monorepo with Tree-sitter into a Memgraph knowledge graph: query it in plain English (NL→Cypher), trace data flow, find dead code, edit via AST-surgical patches.

Local-first code intelligence graph for AI coding tools: Tree-sitter AST graph + blast-radius analysis served over MCP, so agents read ~82x fewer tokens per review question.

Code intelligence MCP in pure C: tree-sitter knowledge graph over 158 languages, average repo indexed in milliseconds, sub-ms queries, 10x fewer tokens. Single static binary, zero deps.

Paste a GitHub URL or drop a local folder → interactive architecture map in the browser: dependency graph, blast radius, health grade, security scan. Single index.html, zero install.
No-train, on-prem code knowledge graph served to AI agents over MCP — symbols, call edges, cross-language links and blast-radius queries, with a hash-chained audit log of every read.
Code-intelligence engine in one static Go binary: tree-sitter graph over 257 languages, compiler-grade resolution for 17, multi-repo, 175 configurable MCP tools — up to 50x fewer tokens. 100% local.

Context layer for large codebases: a graph of plain-English markdown nodes — no embeddings, no index — agents read like any repo file. Claude Code hooks + MCP; 42% fewer tokens in its bench.
A living wiki for your codebase, written by your coding agents: a Tree-sitter graph grounds structured Markdown notes, task-aware routing loads only what's needed, and drift checks catch stale claims.

Desktop app plus MCP server keeping a codebase's ontology as reviewable Markdown in the repo: domains and capabilities linked to code evidence, compiled to a graph for blast-radius queries.

Codebase intelligence for AI and humans: deterministic code-health scores calibrated on real defects, graph-aware refactoring plans agents can execute, auto-docs and git analytics over 9 MCP tools.
Red Hat's 'ripgrep of AI context': a zero-dependency C++23 CLI + MCP that hands a coding agent a ranked call graph — what to touch, blast radius, tests to run — with no index server.
The IDE for your coding agent: an MCP toolkit giving symbol-level retrieval, editing, refactoring and debugging over real language servers — or a JetBrains plugin backend.

Code-intelligence MCP server for coding agents — a pre-indexed semantic graph (libSQL + FTS5) they query instead of grepping: symbols, callers, impact radius in one call. 100% local, 50+ languages.

Plugin for Claude Code and 16 other hosts that turns any codebase into an interactive knowledge graph — multi-agent analysis, layered dashboard, guided tours, diff-impact view, domain mapping.
zg: ripgrep, BM25 and vector search behind one local-first CLI for humans and agents — index a workspace once, search code, docs and data by meaning, then verify with exact text or regex.