Structured Context Storage

Store your project knowledge in a structured SQLite database that is organically used during conversations with your AI. The more you store in Engrams, the less you need to provide in each prompt.

How it works

Every significant fact about your project — a database choice, a coding convention, an architectural pattern — can be stored in Engrams. Your AI retrieves these facts automatically when they become relevant, grounding its responses in your actual project decisions rather than generic assumptions.

Example

You: "Implement a new /medications endpoint that looks for a
      patient_id in the request body and returns their meds.
      Start with authorized GET and POST only."

AI:  Found relevant decisions:
     Decision #23: PostgreSQL is our primary database
     Decision #24: All operations written with SQLAlchemy
     Decision #7:  JWT token authentication

     I'll extract the authenticated user from the request body
     for POST operations. The INSERT and SELECT will use SQLAlchemy.

Product Context vs Active Context

Type	What it stores	How often it changes
Product Context	Project goals, tech stack, architecture overview, key features	Rarely — on major pivots
Active Context	Current focus, open questions, recent changes, next steps	Every session

MCP tools

• get_product_context / update_product_context
• get_active_context / update_active_context
• log_decision / get_decisions / search_decisions_fts
• log_progress / get_progress
• log_system_pattern / get_system_patterns
• log_custom_data / get_custom_data

See the full MCP Tools reference for parameters.