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Code Graph Context

npm version MIT License TypeScript Neo4j NestJS OpenAI MCP

Give your AI coding assistant a photographic memory of your codebase.

Code Graph Context is an MCP server that builds a semantic graph of your TypeScript codebase, enabling Claude to understand not just individual files, but how your entire system fits together.

Config-Driven & Extensible: Define custom framework schemas to capture domain-specific patterns beyond the included NestJS support. The parser is fully configurable to recognize your architectural patterns, decorators, and relationships.

                    ┌─────────────────────────────────────────────────────────────┐
                    │                     YOUR CODEBASE                           │
                    │  ┌──────────┐  ┌──────────┐  ┌──────────┐  ┌──────────┐    │
                    │  │ Service  │  │Controller│  │  Module  │  │  Entity  │    │
                    │  └────┬─────┘  └────┬─────┘  └────┬─────┘  └────┬─────┘    │
                    └───────┼─────────────┼─────────────┼─────────────┼──────────┘
                            │             │             │             │
                            ▼             ▼             ▼             ▼
                    ┌─────────────────────────────────────────────────────────────┐
                    │                   CODE GRAPH CONTEXT                        │
                    │                                                             │
                    │   AST Parser ──► Neo4j Graph ──► Vector Embeddings          │
                    │   (ts-morph)     (Relationships)  (Local or OpenAI)         │
                    │                                                             │
                    └─────────────────────────────────────────────────────────────┘
                                                │
                                                ▼
                    ┌─────────────────────────────────────────────────────────────┐
                    │                      CLAUDE CODE                            │
                    │                                                             │
                    │   "What services depend on UserService?"                    │
                    │   "What's the blast radius if I change this function?"      │
                    │   "Find all HTTP endpoints that accept a UserDTO"           │
                    │   "Refactor this across all 47 files that use it"           │
                    │                                                             │
                    └─────────────────────────────────────────────────────────────┘

Why Code Graph Context?

Without Code Graph

With Code Graph

Claude reads files one at a time

Claude understands the entire dependency tree

"What uses this?" requires manual searching

Instant impact analysis with risk scoring

Refactoring misses edge cases

Graph traversal finds every reference

Large codebases overwhelm context

Semantic search finds exactly what's relevant

Multi-file changes are error-prone

Swarm agents coordinate parallel changes

Features

  • Multi-Project Support: Parse and query multiple projects in a single database with complete isolation

  • Semantic Search: Vector-based search using local or OpenAI embeddings to find relevant code

  • Natural Language Querying: Convert questions into Cypher queries

  • Framework-Aware: Built-in NestJS schema with ability to define custom framework patterns

  • Weighted Graph Traversal: Intelligent traversal scoring paths by importance and relevance

  • Workspace Support: Auto-detects Nx, Turborepo, pnpm, Yarn, and npm workspaces

  • Parallel & Async Parsing: Multi-threaded parsing with Worker threads for large codebases

  • Streaming Import: Chunked processing for projects with 100+ files

  • Incremental Parsing: Only reparse changed files

  • File Watching: Real-time graph updates on file changes

  • Impact Analysis: Assess refactoring risk (LOW/MEDIUM/HIGH/CRITICAL)

  • Dead Code Detection: Find unreferenced exports with confidence scoring

  • Duplicate Detection: Structural (AST hash) and semantic (embedding similarity) duplicates

  • Swarm Coordination: Multi-agent stigmergic coordination with pheromone decay

Architecture

TypeScript Source → AST Parser (ts-morph) → Neo4j Graph + Vector Embeddings → MCP Tools

Core Components:

  • src/core/parsers/typescript-parser.ts - AST parsing with ts-morph

  • src/storage/neo4j/neo4j.service.ts - Graph storage and queries

  • src/core/embeddings/embeddings.service.ts - Embedding service (local sidecar or OpenAI)

  • src/mcp/mcp.server.ts - MCP server and tool registration

Dual-Schema System:

  • Core Schema: AST-level nodes (ClassDeclaration, MethodDeclaration, ImportDeclaration, etc.)

  • Framework Schema: Semantic interpretation (NestController, NestService, HttpEndpoint, etc.)

Nodes have both coreType (AST) and semanticType (framework meaning), enabling queries like "find all controllers" while maintaining AST precision.

Quick Start

Prerequisites

  • Node.js >= 18

  • Python >= 3.10 (for local embeddings)

  • Docker (for Neo4j)

No API keys required. Local embeddings work out of the box using a Python sidecar.

1. Install

npm install -g code-graph-context
code-graph-context init  # Sets up Neo4j + Python sidecar + downloads embedding model

The init command handles everything:

  • Starts a Neo4j container via Docker

  • Creates a Python virtual environment

  • Installs embedding dependencies (PyTorch, sentence-transformers)

  • Downloads the default embedding model (~3GB)

2. Configure Claude Code

claude mcp add --scope user code-graph-context -- code-graph-context

That's it. No API keys needed. Restart Claude Code and you're ready to go.

Want to use OpenAI instead? See Embedding Configuration below.

3. Parse Your Project

In Claude Code, say:

"Parse this project and build the code graph"

Claude will run parse_typescript_project and index your codebase.


Configuration Files

Claude Code stores MCP server configs in JSON files. The location depends on scope:

Scope

File

Use Case

User (global)

~/.claude.json

Available in all projects

Project

.claude.json in project root

Project-specific config

Local

.mcp.json in project root

Git-ignored local overrides

Manual Configuration

If you prefer to edit the config files directly:

~/.claude.json (user scope - recommended):

{
  "mcpServers": {
    "code-graph-context": {
      "command": "code-graph-context"
    }
  }
}

With OpenAI (optional):

{
  "mcpServers": {
    "code-graph-context": {
      "command": "code-graph-context",
      "env": {
        "OPENAI_ENABLED": "true",
        "OPENAI_API_KEY": "sk-your-key-here"
      }
    }
  }
}

From source installation:

{
  "mcpServers": {
    "code-graph-context": {
      "command": "node",
      "args": ["/absolute/path/to/code-graph-context/dist/cli/cli.js"]
    }
  }
}

Environment Variables

Variable

Required

Default

Description

NEO4J_URI

No

bolt://localhost:7687

Neo4j connection URI

NEO4J_USER

No

neo4j

Neo4j username

NEO4J_PASSWORD

No

PASSWORD

Neo4j password

EMBEDDING_MODEL

No

codesage/codesage-base-v2

Local embedding model (see Embedding Configuration)

EMBEDDING_BATCH_SIZE

No

16

Texts per embedding batch (lower = less memory, higher = faster)

EMBEDDING_SIDECAR_PORT

No

8787

Port for local embedding server

EMBEDDING_DEVICE

No

auto (mps/cpu)

Device for embeddings. Auto-detects MPS on Apple Silicon

EMBEDDING_HALF_PRECISION

No

false

Set true for float16 (uses ~0.5x memory)

OPENAI_ENABLED

No

false

Set true to use OpenAI instead of local

OPENAI_API_KEY

No*

-

Required when OPENAI_ENABLED=true


Core Capabilities

Find code by describing what you need, not by memorizing file paths:

"Find where user authentication tokens are validated"
"Show me the database connection pooling logic"
"What handles webhook signature verification?"

Impact Analysis

Before you refactor, understand the blast radius:

┌─────────────────────────────────────────────────────────────┐
│ Impact Analysis: UserService.findById()                     │
├─────────────────────────────────────────────────────────────┤
│ Risk Level: HIGH                                            │
│                                                             │
│ Direct Dependents (12):                                     │
│   └── AuthController.login()                                │
│   └── ProfileController.getProfile()                        │
│   └── AdminService.getUserDetails()                         │
│   └── ... 9 more                                            │
│                                                             │
│ Transitive Dependents (34):                                 │
│   └── 8 controllers, 15 services, 11 tests                  │
│                                                             │
│ Affected Files: 23                                          │
│ Recommendation: Add deprecation warning before changing     │
└─────────────────────────────────────────────────────────────┘

Graph Traversal

Explore relationships in any direction:

UserController
    │
    ├── INJECTS ──► UserService
    │                   │
    │                   ├── INJECTS ──► UserRepository
    │                   │                   │
    │                   │                   └── MANAGES ──► User (Entity)
    │                   │
    │                   └── INJECTS ──► CacheService
    │
    └── EXPOSES ──► POST /users
                        │
                        └── ACCEPTS ──► CreateUserDTO

Dead Code Detection

Find code that can be safely removed:

Dead Code Analysis: 47 items found
├── HIGH confidence (23): Exported but never imported
│   └── formatLegacyDate() in src/utils/date.ts:45
│   └── UserV1DTO in src/dto/legacy/user.dto.ts:12
│   └── ... 21 more
├── MEDIUM confidence (18): Private, never called
└── LOW confidence (6): May be used dynamically

Duplicate Code Detection

Identify DRY violations across your codebase:

Duplicate Groups Found: 8

Group 1 (Structural - 100% identical):
├── validateEmail() in src/auth/validation.ts:23
└── validateEmail() in src/user/validation.ts:45
    Recommendation: Extract to shared utils

Group 2 (Semantic - 94% similar):
├── parseUserInput() in src/api/parser.ts:78
└── sanitizeInput() in src/webhook/parser.ts:34
    Recommendation: Review for consolidation

Swarm Coordination

Execute complex, multi-file changes with parallel AI agents.

The swarm system enables multiple Claude agents to work on your codebase simultaneously, coordinating through the code graph without stepping on each other.

                         ┌──────────────────┐
                         │   ORCHESTRATOR   │
                         │                  │
                         │ "Add JSDoc to    │
                         │  all services"   │
                         └────────┬─────────┘
                                  │
                    ┌─────────────┼─────────────┐
                    │             │             │
                    ▼             ▼             ▼
             ┌──────────┐  ┌──────────┐  ┌──────────┐
             │ Worker 1 │  │ Worker 2 │  │ Worker 3 │
             │          │  │          │  │          │
             │ Claiming │  │ Working  │  │ Claiming │
             │ AuthSvc  │  │ UserSvc  │  │ PaySvc   │
             └──────────┘  └──────────┘  └──────────┘
                    │             │             │
                    └─────────────┼─────────────┘
                                  │
                                  ▼
                    ┌─────────────────────────────┐
                    │      PHEROMONE TRAILS       │
                    │                             │
                    │  AuthService: [claimed]     │
                    │  UserService: [modifying]   │
                    │  PayService:  [claimed]     │
                    │  CacheService: [available]  │
                    │                             │
                    └─────────────────────────────┘

Two Coordination Mechanisms

1. Pheromone System (Stigmergic)

Agents leave markers on code nodes that decay over time—like ants leaving scent trails:

Pheromone

Half-Life

Meaning

exploring

2 min

"I'm looking at this"

claiming

1 hour

"This is my territory"

modifying

10 min

"I'm actively changing this"

completed

24 hours

"I finished work here"

warning

Never

"Don't touch this"

blocked

5 min

"I'm stuck"

Self-healing: If an agent crashes, its pheromones decay and the work becomes available again.

2. Task Queue (Blackboard)

Explicit task management with dependencies:

┌─────────────────────────────────────────────────────────────┐
│                        TASK QUEUE                           │
├─────────────────────────────────────────────────────────────┤
│ [available] Add JSDoc to UserService         priority: high │
│ [claimed]   Add JSDoc to AuthService         agent: worker1 │
│ [blocked]   Update API docs ─────────────────► depends on ──┤
│ [in_progress] Add JSDoc to PaymentService    agent: worker2 │
│ [completed] Add JSDoc to CacheService        ✓              │
└─────────────────────────────────────────────────────────────┘

Swarm Tools

Tool

Purpose

swarm_post_task

Add a task to the queue

swarm_get_tasks

Query tasks with filters

swarm_claim_task

Claim/start/release a task

swarm_complete_task

Complete/fail/request review

swarm_pheromone

Leave a marker on a code node

swarm_sense

Query what other agents are doing

swarm_cleanup

Remove pheromones after completion

Example: Parallel Refactoring

// Orchestrator decomposes the task and creates individual work items
swarm_post_task({
  projectId: "backend",
  swarmId: "swarm_rename_user",
  title: "Update UserService.findUserById",
  description: "Rename getUserById to findUserById in UserService",
  type: "refactor",
  createdBy: "orchestrator"
})

// Workers claim and execute tasks
swarm_claim_task({ projectId: "backend", swarmId: "swarm_rename_user", agentId: "worker_1" })
// ... do work ...
swarm_complete_task({ taskId: "task_1", agentId: "worker_1", action: "complete", summary: "Renamed method" })

Install the Swarm Skill

For optimal swarm execution, install the included Claude Code skill that teaches agents the coordination protocol:

# Copy to your global skills directory
mkdir -p ~/.claude/skills
cp -r skills/swarm ~/.claude/skills/

Or for a specific project:

cp -r skills/swarm .claude/skills/

The skill provides:

  • Worker agent protocol with step-by-step workflow

  • Multi-phase orchestration patterns (discovery, contracts, implementation, validation)

  • Common failure modes and how to prevent them

  • Complete tool reference

Once installed, just say "swarm" or "parallel agents" and Claude will use the skill automatically.

See skills/swarm/SKILL.md for the full documentation.


All Tools

Tool

Description

Discovery

list_projects

List parsed projects in the database

search_codebase

Semantic search using vector embeddings

traverse_from_node

Explore relationships from a node

natural_language_to_cypher

Convert questions to Cypher queries

Analysis

impact_analysis

Assess refactoring risk (LOW/MEDIUM/HIGH/CRITICAL)

detect_dead_code

Find unreferenced exports and methods

detect_duplicate_code

Find structural and semantic duplicates

Parsing

parse_typescript_project

Build the graph from source

check_parse_status

Monitor async parsing jobs

start_watch_project

Auto-update graph on file changes

stop_watch_project

Stop file watching

list_watchers

List active file watchers

Swarm

swarm_post_task

Add task to the queue

swarm_get_tasks

Query tasks

swarm_claim_task

Claim/start/release tasks

swarm_complete_task

Complete/fail/review tasks

swarm_pheromone

Leave coordination markers

swarm_sense

Query what others are doing

swarm_cleanup

Clean up after swarm completion

Utility

test_neo4j_connection

Verify database connectivity

Tool Workflow Patterns

Pattern 1: Discovery → Focus → Deep Dive

list_projects → search_codebase → traverse_from_node → traverse (with skip for pagination)

Pattern 2: Pre-Refactoring Safety

search_codebase("function to change") → impact_analysis(nodeId) → review risk level

Pattern 3: Code Health Audit

detect_dead_code → detect_duplicate_code → prioritize cleanup

Pattern 4: Multi-Agent Work

swarm_post_task → swarm_claim_task → swarm_complete_task → swarm_get_tasks(includeStats) → swarm_cleanup

Multi-Project Support

All query tools require projectId for isolation. You can use:

  • Project ID: proj_a1b2c3d4e5f6 (auto-generated)

  • Project name: my-backend (from package.json)

  • Project path: /path/to/project (resolved automatically)

// These all work:
search_codebase({ projectId: "my-backend", query: "auth" })
search_codebase({ projectId: "proj_a1b2c3d4e5f6", query: "auth" })
search_codebase({ projectId: "/path/to/my-backend", query: "auth" })

Framework Support

NestJS (Built-in)

Deep understanding of NestJS patterns:

  • Controllers with route analysis (@Controller, @Get, @Post, etc.)

  • Services with dependency injection mapping (@Injectable)

  • Modules with import/export relationships (@Module)

  • Guards, Pipes, Interceptors as middleware chains

  • DTOs with validation decorators (@IsString, @IsEmail, etc.)

  • Entities with TypeORM relationship mapping

NestJS-Specific Relationships:

  • INJECTS - Dependency injection

  • EXPOSES - Controller exposes HTTP endpoint

  • MODULE_IMPORTS, MODULE_PROVIDES, MODULE_EXPORTS - Module system

  • GUARDED_BY, TRANSFORMED_BY, INTERCEPTED_BY - Middleware

Custom Framework Schemas

The parser is config-driven. Define your own framework patterns:

// Example: Custom React schema
const REACT_SCHEMA = {
  name: 'react',
  decoratorPatterns: [
    { pattern: /^use[A-Z]/, semanticType: 'ReactHook' },
    { pattern: /^with[A-Z]/, semanticType: 'HOC' },
  ],
  nodeTypes: [
    { coreType: 'FunctionDeclaration', condition: (node) => node.name?.endsWith('Provider'), semanticType: 'ContextProvider' },
  ],
  relationships: [
    { type: 'PROVIDES_CONTEXT', from: 'ContextProvider', to: 'ReactHook' },
  ]
};

The dual-schema system means every node has:

  • coreType: AST-level (ClassDeclaration, FunctionDeclaration)

  • semanticType: Framework meaning (NestController, ReactHook)

This enables queries like "find all hooks that use context" while maintaining AST precision for refactoring.


Embedding Configuration

Local embeddings are the default — no API key needed. The Python sidecar starts automatically on first use and runs a local model for high-quality code embeddings.

The sidecar uses MPS (Apple Silicon GPU) when available, falling back to CPU. It auto-shuts down after 3 minutes of inactivity to free memory, and restarts lazily when needed (~15-20s).

Device override: Set EMBEDDING_DEVICE=cpu to force CPU if MPS causes issues.

Half precision: Set EMBEDDING_HALF_PRECISION=true to load the model in float16, roughly halving memory usage.

Available Models

Set via the EMBEDDING_MODEL environment variable:

Model

Dimensions

RAM (fp16)

Quality

Best For

codesage/codesage-base-v2 (default)

1024

~700 MB

Best

Default, code-specific encoder, fast

Qodo/Qodo-Embed-1-1.5B

1536

~4.5 GB

Great

Machines with 32+ GB RAM

BAAI/bge-base-en-v1.5

768

~250 MB

Good

General purpose, low RAM

sentence-transformers/all-MiniLM-L6-v2

384

~100 MB

OK

Minimal RAM, fast

nomic-ai/nomic-embed-text-v1.5

768

~300 MB

Good

Code + prose mixed

sentence-transformers/all-mpnet-base-v2

768

~250 MB

Good

Balanced quality/speed

BAAI/bge-small-en-v1.5

384

~65 MB

OK

Smallest footprint

Example: Use a lightweight model on a low-memory machine:

claude mcp add --scope user code-graph-context \
  -e EMBEDDING_MODEL=BAAI/bge-base-en-v1.5 \
  -- code-graph-context

Switching Models

Switching models requires re-parsing — vector index dimensions are locked per model. Drop existing indexes first:

DROP INDEX embedded_nodes_idx IF EXISTS;
DROP INDEX session_notes_idx IF EXISTS;

Then re-parse your project with the new model configured.

Using OpenAI Instead

If you prefer OpenAI embeddings (higher quality, requires API key):

claude mcp add --scope user code-graph-context \
  -e OPENAI_ENABLED=true \
  -e OPENAI_API_KEY=sk-your-key-here \
  -- code-graph-context

Troubleshooting

MCP Server Not Connecting

# Check the server is registered
claude mcp list

# Verify Neo4j is running
docker ps | grep neo4j

# Test manually
code-graph-context status

Embedding Errors

"Failed to generate embedding" — The local sidecar may not have started. Check:

# Verify Python deps are installed
code-graph-context status

# Re-run init to fix sidecar setup
code-graph-context init

Out of memory (large model on 16GB machine) — Switch to a lighter model:

claude mcp add --scope user code-graph-context \
  -e EMBEDDING_MODEL=BAAI/bge-base-en-v1.5 \
  -- code-graph-context

Using OpenAI and getting auth errors — Ensure your key is configured:

claude mcp remove code-graph-context
claude mcp add --scope user code-graph-context \
  -e OPENAI_ENABLED=true \
  -e OPENAI_API_KEY=sk-your-key-here \
  -- code-graph-context

Neo4j Memory Issues

For large codebases, increase memory limits:

# Stop and recreate with more memory
code-graph-context stop
code-graph-context init --memory 4G

Parsing Timeouts

Use async mode for large projects:

parse_typescript_project({
  projectPath: "/path/to/project",
  tsconfigPath: "/path/to/project/tsconfig.json",
  async: true  // Returns immediately, poll with check_parse_status
})

CLI Commands

code-graph-context init [options]   # Set up Neo4j + Python sidecar + embedding model
code-graph-context status           # Check Docker/Neo4j/sidecar status
code-graph-context stop             # Stop Neo4j container

Init options:

  • -p, --port <port> - Bolt port (default: 7687)

  • --http-port <port> - Browser port (default: 7474)

  • --password <password> - Neo4j password (default: PASSWORD)

  • -m, --memory <size> - Heap memory (default: 2G)

  • -f, --force - Recreate container


Contributing

git clone https://github.com/drewdrewH/code-graph-context.git
cd code-graph-context
npm install
npm run build
npm run dev  # Watch mode

Conventional Commits: feat|fix|docs|refactor(scope): description


License

MIT - see LICENSE


-
security - not tested
A
license - permissive license
-
quality - not tested

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