What is MemContext?
MemContext is memory infrastructure for AI agents and applications. It provides a REST API and MCP server that allow AI systems to:- Save durable user and project knowledge across sessions
- Search memories using hybrid retrieval (vector + full-text)
- Evolve memories over time with automatic version chains
- Profile users with pre-aggregated context from their memory
Who is it for?
MemContext serves two primary use cases:- Coding assistants that need stable preferences, decisions, and project context across sessions
- Product applications that need evolving memory for content generation, support, onboarding, or personalization
Core primitives
| Concept | Description |
|---|---|
| Category | Broad memory type: preference, fact, decision, or context |
| Project | Scope boundary for project-specific memories |
| Version chains | Memories can supersede old memories without losing history |
| Hybrid search | Vector similarity + keyword search merged with Reciprocal Rank Fusion |
| MCP tools | AI assistants can save and search memory directly via Model Context Protocol |
Why it exists
Plain vector search is not enough for memory. Memory needs:- Updates when reality changes
- History when strategy evolves
- Exact-match retrieval for product names, org names, and decisions
- Lightweight APIs other tools can build on
Next steps
Quickstart
Make your first API and MCP calls in under 2 minutes.
How It Works
Understand the save flow, classification, and search pipeline.
API Reference
Full endpoint documentation with interactive examples.
MCP Setup
Connect MemContext to Claude Desktop, Cursor, or any MCP client.