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1. Get an API key

Sign up at app.memcontext.in and create an API key from Settings > API Keys. Your key will look like mc_abc123... and is shown only once - store it securely.

2. Save a memory

Response:
The status field tells you what happened: Longer notes may return 202 Accepted with a jobId and message for tracking extraction into atomic memories.

3. Search memories

Response:
Use full natural-language sentences as queries for best results. Keywords alone reduce match quality.

4. Save a scope-isolated memory

Use scope when one API key serves multiple end users or tenants. Omit it only for global, unscoped memories.

5. Save a project memory inside that scope

6. Connect the MCP server

For Claude.ai or Claude Desktop, add a custom connector with:
Then click Connect, sign in to MemContext, and approve access. For coding assistants, you can still connect MemContext directly. For example, with Claude Code:
No local installation required. Once connected, your assistant can call save_memory and search_memory directly. See MCP Setup for Claude.ai, Claude Desktop, Cursor, OpenCode, Codex CLI, and agent instructions.

TypeScript SDK

Install the SDK when integrating from a Node.js or TypeScript app:
Use withScope() for the hard end-user or tenant boundary. Use withProject() only as a grouping filter inside that scope.
  1. Search first - check for existing context before making assumptions
  2. Save when durable - persist stable preferences, decisions, and project facts
  3. Use categories - tag memories so they can be filtered later
  4. Use scope - isolate each app user or tenant into its own memory container
  5. Use projects - group project-specific knowledge inside that scope
  6. Give feedback - mark retrieved memories as helpful or outdated to improve quality