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Roadmap

Roadmap

Phase 1 — MCP Server MVP ✅ Shipped

The foundation: a working MCP server with full conversation storage and semantic search. Live at mcp.getengram.app.

  • Monorepo setup (pnpm workspaces + Turborepo)
  • Shared types, Zod schemas, and utilities
  • D1 database schema + indexes
  • Typed query helpers for all tables
  • MCP server with core memory tools
  • API key authentication (SHA-256 hashed)
  • Sliding-window message chunking
  • Embedding generation via Workers AI
  • Vectorize semantic search with org-scoped filtering
  • Tenant isolation at every layer
  • Comprehensive test suite
  • Deploy to Cloudflare Workers
  • Production API key provisioning

Phase 2 — API and Operations ✅ Shipped

Management capabilities beyond the MCP protocol.

  • Rate limiting per organization
  • Usage tracking and metering
  • Webhook notifications (conversation created, messages appended)
  • Conversation exports
  • API key management (create, list, revoke)
  • Public REST API for data (append/search over HTTP without MCP)
  • Bulk operations (bulk delete)

Phase 3 — Dashboard and Teams ✅ Shipped

A web interface for managing Engram without touching code.

  • Dashboard UI
  • OAuth 2.1 authorization server (self-serve app connections, e.g. ChatGPT)
  • Team management (seats, billing, connected apps)
  • API key management UI
  • Connected-apps management (list + revoke)
  • Conversation browser — view and search conversations in the UI
  • Analytics — message volume, search patterns, active agents

Phase 4 — In progress

  • Admin dashboard — business metrics and operational visibility
  • ChatGPT plugin directory listing (public, no Developer mode required)
  • Deterministic capture adapters for more hosts (Cursor hooks, etc.)
  • Enterprise history backfill for ChatGPT Business/Enterprise workspaces

Future Considerations

  • Async embedding pipeline — Move chunking/embedding to Cloudflare Queues to reduce append latency
  • Configurable chunking — Let users tune window size and stride per organization
  • Multiple embedding models — Support larger/multilingual models
  • Cross-conversation search — Search with conversation-level context (not just chunk-level)
  • Conversation branching — Fork conversations for A/B testing agent responses
  • Retention policies — Automatic cleanup of old conversations by age or count
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