Inspired buildLocal-firstCode knowledge graphMCP integration

CodeAtlas

A local context service that gives coding agents a persistent map of the repository. CodeAtlas extracts symbols and structural relationships, then serves focused graph neighborhoods for debugging, review, impact analysis, and implementation work without uploading the codebase.

Origin: Inspired build
Role: Product, design & technology
Focus: Application
Engineering Area: AI & ML
Domain: Developer & education
Status: Prototyped

Why this should exist

Coding agents need a map of the repository before they need more tokens

AI coding tools often search one file at a time and rebuild the same context for every task. CodeAtlas keeps a local graph of symbols and relationships so an agent can ask a bounded question and receive the relevant neighborhood.

Problem and product

The problems

01
Repository context is rebuilt repeatedly across coding tasks.
02
Text search cannot reliably explain symbol relationships or change impact.
03
Cloud indexing creates privacy concerns for proprietary code.

What the product delivers

Builds persistent code knowledge graphs from local repositories
Extracts symbols and structural relationships across Python, Java, JavaScript, TypeScript, JSX, and TSX
Supports symbol lookup, impact analysis, bounded context retrieval, and graph-neighborhood traversal
Performs full builds and changed-file incremental graph updates
Stores graph state locally in SQLite with full-text search
Exposes a CLI and stable MCP tools for Codex and other agent clients

Technology used

A stack chosen for the product

Tree-sitter extracts symbols and edges across multiple languages. SQLite stores the local graph and full-text index, FastAPI exposes query services, and stable MCP tools deliver bounded context to coding agents.

PythonFastAPIReactViteSQLiteFTSTree-sitterMCPKnowledge GraphCLI

Architecture

How the system holds together

01
Repository indexer
Full and incremental scans parse code into symbols, files, calls, imports, and structural relationships.
02
Local knowledge graph
SQLite and full-text search keep repository intelligence fast, inspectable, and private.
03
Agent interface
CLI, API, and MCP tools expose lookup, impact analysis, and graph-neighborhood queries.

Estimated goals

A local context service for serious coding-agent workflows

The inspired build can grow through measurable improvements to navigation, impact analysis, and agent task completion across real repositories.

01
Benchmark context precision across large multi-language repositories.
02
Measure whether graph retrieval improves coding-agent task outcomes.
03
Add language support and integrations without weakening local-first operation.

Future goals are directional estimates and depend on user validation.

Extras

Product perspective

Primary audience: Developers and teams using AI coding agents
Origin: Inspired build created to study local code knowledge graphs
Product edge: Persistent local structure replaces repeated full-repository context gathering

Execution principle

Validate the narrow customer promise first. Add scope only when evidence shows that it improves the outcome.

Full project notes

Product and engineering deep dive

The project overview adds a concise presentation layer. The complete product details remain below.

From intent to implementation

A product direction shaped around a real use case.

A local-first code knowledge graph for AI-assisted software development that scans repositories, extracts structural relationships, and serves bounded context for debugging, review, impact analysis, and coding-agent workflows.

01 · The product response

What people can do with it

Builds persistent code knowledge graphs from local repositories
Extracts symbols and structural relationships across Python, Java, JavaScript, TypeScript, JSX, and TSX
Supports symbol lookup, impact analysis, bounded context retrieval, and graph-neighborhood traversal
Performs full builds and changed-file incremental graph updates
Stores graph state locally in SQLite with full-text search
Exposes a CLI and stable MCP tools for Codex and other agent clients
Includes FastAPI services plus React dashboard views for repository insights, 2D and 3D graph exploration, and code queries

Project sponsorship

Fund this project—from prototype to production.

Help move CodeAtlas from a promising prototype to a reliable production release.

Design validation and user research
Production infrastructure and security
Testing, accessibility, and launch readiness

Choose a sponsorship amount

Your sponsorship₹1,000

₹100₹1,00,000

Secure checkout by Razorpay. Sponsorship does not provide equity, ownership, or a guaranteed delivery date.

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