In Memoria: Persistent Codebase Intelligence

In Memoria is an MCP server that learns your codebase patterns once, then exposes that intelligence to AI agents persistently. Instead of re-analyzing code on every interaction, it maintains a semantic understanding of your architecture, conventions, and decisions.

Core Concept

Setup → Learn → Verify → Serve. After that, AI agents query persistent intelligence without repeated parsing.

Quick Start (5 minutes)

1. Configure for your project

npx in-memoria setup --interactive

2. Build intelligence database

npx in-memoria learn ./src

3. Verify it worked

npx in-memoria check ./src --verbose

4. Keep it fresh (optional but recommended)

npx in-memoria watch ./src

5. Expose to agents via MCP

npx in-memoria server

When to Use

✅ Use In Memoria:

• Building long-lived AI agent partnerships (Claude, Copilot, etc.)

• Projects where consistency across sessions matters

• Teams wanting shared codebase intelligence

❌ Skip it:

• One-off analysis (use npx in-memoria analyze [path] directly)

• Simple projects agents can read directly

The 5 Core Commands

Command Purpose When

setup --interactive

Configure exclusions, paths, preferences First time only

learn [path]

Build/rebuild intelligence database After setup, major refactors

check [path]

Validate intelligence layer After learn, before server

watch [path]

Auto-update intelligence on code changes During development (optional)

server

Start MCP server for agent queries After check passes

Key difference: learn builds persistent knowledge. analyze is one-time reporting only.

What Agents See

When connected, agents can query:

• Project structure - Tech stack, entry points, architecture

• Code patterns - Your naming conventions, error handling, patterns used

• Smart routing - "Add password reset" → suggests src/auth/password-reset.ts

• Semantic search - Find code by meaning, not keywords

• Work context - Track decisions, tasks, approach consistency

Troubleshooting

Issue Fix

Learn fails Verify path is correct; check file permissions

Check reports missing intelligence Run learn [path] again

Agent doesn't see new code Is watch running? Start it: npx in-memoria watch ./src

Server won't start Run check --verbose first; if issues, rebuild: rm .in-memoria/*.db && npx in-memoria learn ./src

Multiple projects conflict Use server --port 3001 (or different port per project)

Performance Notes

• Small projects (<1K files): 5-15s to learn

• Medium (1K-10K files): 30-60s

• Large (10K+ files): 2-5min

If learning stalls (>10min), verify you're not indexing node_modules/ , dist/ , or build artifacts—use setup's exclusion patterns.

Key Principles

• Local-first - Everything stays on your machine; no telemetry

• Persistent - One learning pass; intelligence updates incrementally with watch

• Agent-native - Designed for MCP; works with Claude, Copilot, and any MCP-compatible tool

• Pattern-based - Learns from your actual code, not rules you define

Deployment Pattern (3 terminals)

Terminal 1: One-time setup

npx in-memoria setup --interactive npx in-memoria learn ./src npx in-memoria check ./src --verbose

Terminal 2: Keep intelligence fresh

npx in-memoria watch ./src

Terminal 3: Expose to agents

npx in-memoria server

Now agents (Claude, Copilot, etc.) have persistent codebase context

See GitHub for full API docs and agent integration examples.