Navegador v0.7¶

The project knowledge graph for AI coding agents.

Navegador builds and maintains a queryable graph of your software project — combining static code analysis with human-curated business knowledge — so that AI coding agents always have precise, structured context instead of raw file dumps.

navegador — Spanish for navigator / sailor. It helps agents navigate your code.

Current version: 0.7.0

Two layers, one graph¶

┌─────────────────────────────────────────────────────────────────┐
│  KNOWLEDGE LAYER                                                │
│  Concepts · Rules · Decisions · WikiPages · People · Domains   │
│                                                                 │
│         ↕  GOVERNS / IMPLEMENTS / DOCUMENTS / ANNOTATES        │
│                                                                 │
│  CODE LAYER                                                     │
│  Repository · File · Module · Class · Function · Method        │
│  Variable · Import · Decorator · (call graphs, hierarchies)    │
└─────────────────────────────────────────────────────────────────┘
              stored in FalkorDB  (SQLite local / Redis prod)

The code layer is populated automatically by ingesting source trees. 13 languages are supported via tree-sitter (Python, TypeScript, JavaScript, Go, Rust, Java, Kotlin, C#, PHP, Ruby, Swift, C, C++). The knowledge layer is populated by manual curation (navegador add), GitHub wiki ingestion, and Planopticon output (meeting and video knowledge graphs).

Quick start¶

pip install navegador              # Python 3.12+ required
navegador ingest ./my-repo         # parse + index the codebase
navegador explain AuthService      # what is this thing?
navegador search "rate limit" --all  # search code + knowledge together

Or use the Python SDK:

from navegador import Navegador

nav = Navegador(".navegador/navegador.db")
nav.ingest("./my-repo")
bundle = nav.explain("AuthService")
print(bundle.to_markdown())

What goes in the graph¶

Layer	Node type	Populated by
Code	Repository, File, Module	`navegador ingest`
Code	Class, Function, Method	`navegador ingest` (tree-sitter AST)
Code	Decorator, Import, Variable	`navegador ingest`
Code	CALLS / INHERITS edges	`navegador ingest` (call graph analysis)
Knowledge	Concept, Domain	`navegador add concept` / `add domain`
Knowledge	Rule	`navegador add rule`
Knowledge	Decision	`navegador add decision`
Knowledge	Person	`navegador add person`
Knowledge	WikiPage	`navegador wiki ingest`
Knowledge	(any)	`navegador planopticon ingest`
Cross-layer	ANNOTATES, GOVERNS, IMPLEMENTS	`navegador annotate`
Analysis	TESTS, COUPLED_WITH edges	`navegador testmap`, `navegador cycles`

Agent integration¶

CLIMCPBootstrapEditor integrationCI/CD

The simplest integration: call navegador explain or navegador context from any shell script or agent tool definition.

# get context for the file the agent just edited
navegador context src/auth/service.py --format json

# look up a function before editing it
navegador function validate_token --depth 2 --format json

# find everything annotated with a business concept
navegador concept PaymentProcessing --format json

Run navegador as a Model Context Protocol server. Configure it once in your agent settings and all navegador commands become callable tools with structured input/output.

{
  "mcpServers": {
    "navegador": {
      "command": "navegador",
      "args": ["mcp"]
    }
  }
}

11 tools available. See MCP Integration for the full tool list and per-agent config snippets. Use --read-only mode to restrict agents to query-only access.

One command to install navegador, ingest a repo, and wire the agent hook for your preferred AI coding assistant.

./bootstrap.sh --repo owner/repo --wiki --agent claude

Supports --agent claude, --agent gemini, and --agent openai. See Agent Hooks for what the hook does and how to configure it manually.

Wire navegador into your editor with one command:

navegador editor setup claude-code
navegador editor setup cursor
navegador editor setup codex
navegador editor setup windsurf

Run navegador in CI pipelines for automated context checks:

navegador ci ingest
navegador ci stats
navegador ci check

What's new in 0.7.0¶

Feature	Command / API
13 languages (added Kotlin, C#, PHP, Ruby, Swift, C, C++)	`pip install "navegador[languages]"`
Python SDK	`from navegador import Navegador`
Incremental ingestion	`navegador ingest --incremental`, `--watch`
Schema migrations	`navegador migrate`
Export / import	`navegador export`, `navegador import` (JSONL)
Editor integrations	`navegador editor setup <editor>`
Analysis commands	`navegador diff`, `navegador churn`, `navegador impact`, `navegador trace`, `navegador deadcode`, `navegador cycles`, `navegador testmap`
Multi-repo	`navegador repo add/list/ingest-all/search`
Semantic search	`navegador semantic-search`, `navegador ask`
Framework enrichment	Django, FastAPI, React, Rails, Spring Boot, Laravel, and more
Monorepo support	Turborepo, Nx, Yarn, pnpm, Cargo, Go workspaces
Cluster mode	Shared Redis graph, pub/sub, task queue, sessions
11 MCP tools (was 7)	`get_rationale`, `find_owners`, `search_knowledge`, `blast_radius` added
Sensitive content redaction	`navegador ingest --redact`
Shell completions	`navegador completions bash/zsh/fish`

Navegador