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Unified code + documentation knowledge graph from Sphinx builds and Python AST analysis

Project description

sphinxcontrib-nexus

A unified code + documentation knowledge graph extracted from Sphinx builds and Python AST analysis. Queryable via MCP, CLI, and Python API.

What makes it unique: Nexus is the only tool that puts code structure (call graphs, imports, inheritance, type annotations) and documentation structure (equations, cross-references, citations, theory pages) in the same graph. This enables queries that are impossible with code-only or doc-only tools — like tracing from a literature citation through an equation to the function that implements it.

Quick Start

pip install sphinxcontrib-nexus

As a Sphinx Extension

Add to your docs/conf.py:

extensions = ['sphinxcontrib.nexus']

After sphinx-build, find the graph at <outdir>/_nexus/graph.db (SQLite) and <outdir>/_nexus/graph.json.

Standalone AST Analysis (no Sphinx needed)

nexus analyze src/ --db graph.db

MCP Server (for Claude Code / AI agents)

nexus serve --db graph.db --project-root /path/to/project

Install Skills + MCP Server for Claude Code

nexus setup           # project-level: .mcp.json + .claude/skills/
nexus setup --global  # user-level: ~/.claude.json + ~/.claude/skills/ (all projects)

Ingest a Paper

nexus ingest paper.pdf --db graph.db     # extracts concepts, equations, citations via LLM

Interactive Graph Visualizer

nexus visualize --db graph.db            # opens HTML graph explorer in browser

Configuration

Config value Default Description
nexus_output _nexus Output directory relative to build output
nexus_ast_analyze True Run AST analysis during Sphinx build
nexus_max_viz_nodes 300 Max nodes in auto-generated graph.html

Supported Project Layouts

Nexus works with any Python project:

  • Standard packages: myproject/mypackage/__init__.py — detected automatically
  • src layout: src/mypackage/ — detected automatically
  • Flat modules: directories with .py files but no __init__.py — detected automatically
  • Custom sys.path: projects that add directories to sys.path in conf.py — picked up from the Sphinx build environment

What the Graph Contains

Node Types (16)

Type Source Example
file Sphinx RST/doc pages
section Sphinx Labeled sections (:ref: targets)
equation Sphinx Labeled math equations (:eq: targets)
term Sphinx Glossary terms
function Sphinx + AST Python functions
class Sphinx + AST Python classes
method Sphinx + AST Python methods
attribute Sphinx + AST Class attributes
module Sphinx + AST Python modules
data Sphinx Module-level data
exception Sphinx Exception classes
type Sphinx Type aliases
external Auto-detected stdlib, builtins, installed packages (numpy, scipy, ...)
unresolved Auto-detected Referenced but not documented symbols

Edge Types (13)

Edge Meaning Source
contains Parent → child (toctree, module→function, class→method) Sphinx + AST
references Cross-reference (:ref:, :term:) Sphinx
documents Doc page → code symbol (:func:, :class:) Sphinx
equation_ref Doc → equation (:eq:) Sphinx
cites Doc → citation Sphinx
implements Code → equation (inferred from co-occurrence in docs) Merge
calls Function → function AST
imports Module → module AST
inherits Class → parent class AST
type_uses Function → type (from annotations) AST
tests Test → tested function AST
derives Derivation → equation AST

MCP Tools (20)

Exploration

  • query — keyword search across node names
  • context — 360-degree view of a symbol (all connections grouped by type)
  • neighbors — direct connections with direction and type filtering
  • shortest_path — how two concepts connect
  • god_nodes — most connected nodes (entry points)
  • stats — graph-level statistics

Safety & Refactoring

  • impact — blast radius analysis (what breaks if you change X)
  • detect_changes — map git diff to affected symbols
  • rename — safe multi-file rename with confidence tagging
  • retest — minimum set of tests to re-run after changes
  • communities — detect functional groupings with cohesion scores
  • graph_query — Cypher-like pattern matching ("function -calls-> function")
  • bridges — find architectural hotspots connecting communities

Code + Doc Fusion (unique to Nexus)

  • provenance_chain — citation → equation → code traceability
  • verification_coverage — equation → code → test coverage map
  • staleness — detect docs that drifted from code
  • session_briefing — AI agent context restoration
  • trace_error — trace from failing test to equations on call path
  • migration_plan — plan dependency migration with phased blast radius
  • ingest — LLM-powered paper/PDF ingestion into the graph
  • processes — detect named execution flows through the codebase

MCP Resources (4)

Resource Content
nexus://graph/stats Node/edge counts by type
nexus://graph/communities Functional area summaries
nexus://graph/schema Node types, edge types, ID format
nexus://briefing Session briefing for AI agents

Skills (8)

Installed via nexus setup. Each skill triggers on natural language:

Skill Triggers on
nexus-exploring "How does X work?", "What calls this?"
nexus-impact "Is it safe to change X?", "What tests to re-run?"
nexus-debugging "Why is X failing?", "Which equation is wrong?"
nexus-refactoring "Rename this", "Extract this into a module"
nexus-verification "What's verified?", "Which docs are stale?"
nexus-migration "Plan numpy→jax migration"
nexus-guide "What Nexus tools are available?"
nexus-cli "Analyze the codebase", "Start the server"

Storage

The graph is stored in two formats:

  • SQLite (primary) — indexed queries, FTS5 full-text search, 0.05ms neighbor lookups
  • JSON (secondary) — human-readable, NetworkX node-link format

Python API

from sphinxcontrib.nexus.export import load_sqlite
from sphinxcontrib.nexus.query import GraphQuery

kg = load_sqlite("_nexus/graph.db")
q = GraphQuery(kg)

# What uses numpy.ndarray?
q.query("ndarray", node_types=["external"])

# Blast radius of changing a function
q.impact("py:function:sn_solver.solve_sn", direction="upstream")

# Citation → equation → code chain
q.provenance_chain("py:function:sn_sweep.sweep_spherical")

# Migration plan
q.migration_plan("numpy", "jax")

License

MIT

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