AI can read your code.
But it doesn't always know why your project became what it is.
Contorium gives AI coding tools a persistent layer of project intelligence — preserving decisions, reasoning, constraints, structure, history, and evolving project state across sessions, tools, and models.
Not chat history. Not prompts. Project intelligence.
Website · Documentation · Overview
Git remembers what changed.
Contorium remembers why.
AI coding agents are getting better at writing and modifying code.
But long-lived projects have another problem:
The codebase contains what the project is — but not always why it became that way.
Important knowledge gets lost between:
- AI sessions
- different coding tools
- model switches
- experiments and failed approaches
- architectural decisions
- long development cycles
Eventually, developers end up explaining the same project to AI again and again.
You should be building the project — not repeatedly explaining it.
A project is more than its files.
It has:
Intent
↓
Decisions
↓
Reasoning
↓
Implementation
↓
Outcomes
↓
Evolution
↓
Current State
Contorium preserves and connects this information so AI tools can work from the project's accumulated understanding instead of reconstructing it from scratch every session.
Decisions
What was chosen, rejected, or changed?
Reasoning
Why was a particular approach taken?
Constraints
What must remain true, and why?
Structure
How are the project's modules, files, and functions connected?
History
How did the project evolve?
Current State
What matters now, and what should happen next?
Your AI tools can change.
Your project's accumulated understanding shouldn't have to.
Your Project
│
▼
┌──────────────────────┐
│ Contorium │
│ │
│ Project Intelligence │
│ Layer │
└──────────┬───────────┘
│
┌──────────┼──────────┐
▼ ▼ ▼
Cursor Claude Codex
│ Code │
│ │ │
└──────────┼──────────┘
▼
Shared Understanding
Use the tools you prefer without forcing each one to reconstruct the project from zero.
Contorium currently integrates with:
- Cursor
- Claude Code
- Gemini CLI
- Codex
- VS Code
- MCP-compatible AI tools
Keep project intelligence across:
- sessions
- tools
- model switches
- long development cycles
The goal is not to remember everything.
The goal is to preserve what matters.
Contorium builds structured relationships across the project:
Intent
↓
Module
↓
File
↓
Function
↓
Dependency
Instead of treating a repository as a collection of disconnected files, Contorium builds a queryable representation of how the project fits together.
Understand how the project evolved.
Track the changes that matter and connect them to the project's broader state.
Preserve the knowledge that is usually lost after a conversation ends:
- what was decided
- what alternatives were considered
- why an approach was chosen
- what happened afterward
This helps future AI sessions understand not only what exists, but why.
Projects evolve. Knowledge becomes outdated.
Contorium tracks whether decisions still hold:
Change → Assumption → Impact → Decision Validity
Lifecycle states include:
VALID → WARNING → DECAYING → SUSPECTED_INVALID → NEEDS_REVALIDATION → INVALIDATED
Ask:
contorium ask "What decisions need review?"Generate a compact representation of the project's current state for AI handoff.
Instead of:
New session
↓
Read everything again
↓
Reconstruct context
↓
Start working
Contorium enables:
New session
↓
Read project intelligence
↓
Understand current state
↓
Continue working
Contorium makes project intelligence accessible to both developers and AI agents.
contorium ask "Why was MCP added?"
contorium ask "What changed recently?"
contorium ask "What do we know about authentication?"
contorium ask "Is this decision still valid?"The goal is not simply retrieving text.
It is connecting the relevant pieces of project knowledge.
Workspace Activity
↓
Collection
↓
Parsing
↓
Project Structure
↓
Knowledge Graph
↓
Intent & State
↓
Project Intelligence
↓
AI-ready Context / Handoff
↓
Any AI Tool
Contorium stores project intelligence locally inside:
.contora/
The project carries its own accumulated understanding instead of tying it to a particular AI provider or session.
Contorium separates project intelligence from the AI tool using a local, structured architecture.
AI Tools (Cursor · Claude · Codex · …)
│
▼
IDE · MCP · CLI (adapters)
│
▼
CIL — Cognitive Interaction Layer
│
▼
PIL — Project Intelligence Layer
│
▼
.contora/
CIL is the interaction layer between AI agents, developers, and project intelligence.
It provides the mechanisms needed to query, capture, and transfer project knowledge.
It is architecture — not the product brand.
The deterministic local store of structured project intelligence:
STATE · INTENT · DECISION · WHY
TIMELINE · IMPACT · PROVENANCE · CONFIDENCE
PIL does not reason. It preserves.
The intelligence stays with the project.
Local-first. Project-centric. Portable.
Deeper guides: docs/OVERVIEW.md · docs/PIL_RUNTIME.md · docs/CIL.md
| Operation | Meaning |
|---|---|
| Capture | Record focus, notes, decisions |
| Inspect | Explore state, decisions, timeline, health |
| Transfer | Export compact context into a new AI session |
contorium capture decision
contorium inspect state
contorium transfer context
contorium ask "What is this project becoming?"Contorium is related to AI memory — but it is not intended to be just another chat-memory or retrieval system.
| System | Primarily preserves |
|---|---|
| Chat Memory | Conversations |
| RAG | Retrieved information |
| Git | Code and file history |
| Context Files | Explicit instructions |
| Contorium | Project intelligence |
The goal is to connect:
What changed
↓
Why it changed
↓
What happened
↓
What remains true
↓
What comes next
Memory is a capability. Project Intelligence is the goal.
Contorium is not:
- an autonomous coding agent
- a replacement for your AI coding tool
- a task generator
- a system that decides what you should build
- a replacement for Git
The developer remains in control.
Contorium preserves project understanding so humans and AI can work from the same evolving state.
- Node.js 18+
- npm
- VS Code / Cursor for the IDE extension
- An MCP-compatible AI tool for MCP integration
git clone https://github.com/ContoriumLabs/contorium.git
cd contorium
npm install
npm run compilenpm run vsixThen:
- Open Extensions
- Select Install from VSIX
- Choose the generated
.vsix - Reload the window
- Open your project
- Set the current focus
- Transfer AI-ready project context when needed
Full guide: docs/IDE_EXTENSION.md · docs/INSTALL.md
Expose project intelligence to MCP-compatible AI tools:
npm install -g @contorium/mcpclaude mcp add --scope project contorium -- npx @contorium/mcpcodex mcp add contorium -- npx @contorium/mcpSet the workspace when needed:
CONTORIUM_WORKSPACE=/path/to/projectPreferred agent operations include:
ask_project
transfer_project
inspect_state · inspect_intent · inspect_decision
capture_focus · capture_note · capture_decision
get_knowledge_health · get_review_queue
Full guide: docs/MCP.md · packages/mcp/README.md
npx contorium init .
npx contorium sync .
npx contorium ask "What is this project?"
npx contorium transfer context
npx contorium lifecycle
npx contorium review
npx contorium status .Full guide: docs/CLI.md
To remove the local project intelligence store:
rm -rf .contoraRemove-Item -Recurse -Force .contoraThe project is the source of truth.
Project understanding should survive sessions, tools, and model changes.
Relationships between decisions, code, intent, and history matter more than isolated text.
AI can understand the project. Humans decide what the project becomes.
Project intelligence should stay close to the project and remain portable.
Contorium works without LLMs.
Optional AI improves explanation, story, essence, and suggested questions.
AI is an interpreter — not the source of truth.
See docs/AI_LAYER.md.
AI coding is moving beyond one-shot code generation toward long-running, multi-agent development.
As agents become more capable, another layer becomes increasingly important:
the project's own intelligence.
The future of AI-assisted development may not be:
Human → AI → Code
but:
Project Intelligence
↙ ↓ ↘
Agent A Agent B Agent C
↘ ↓ ↙
Project
Different models and tools can change.
The project's accumulated understanding should not have to.
AI can write the code.
Contorium helps it understand the project.
Documentation: docs/README.md · Install · Overview
Website: https://www.contorium.dev
GitHub: https://github.com/ContoriumLabs/contorium
License: MIT