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Engram

Persistent, verbatim, searchable memory for AI assistants — one memory across every MCP client.

AI 与智能体15In the official Registryv0.1.0

Install

Add --scope user to use it in every project.

Remote server (http)

claude mcp add --transport http engram https://mcp.getengram.app/mcp

README

Engram

Memory infrastructure for AI agents. Store every conversation verbatim. Search by meaning.

Website Docs License

Engram is an MCP-native memory server that stores complete, uncompressed conversation transcripts and makes them searchable via semantic search. Connect any MCP-compatible client — Claude Desktop, Claude Code, Cursor, Windsurf, Zed — and your agent remembers everything across sessions.

Quick start

Claude Code

/plugin marketplace add get-engram/engram
/plugin install engram@engram

Restart Claude Code and approve access in the browser. There is no API key to copy and no config file to edit — the server implements the MCP authorization flow (RFC 9728 / 8414 / 7591, PKCE), so the client discovers it, registers itself, and signs you in. A free account is created as part of signing in.

The plugin also ships a skill that tells Claude when to search memory and what is worth saving, so context accumulates without being asked.

Any other MCP client

Point it at the remote server and let OAuth handle access:

{
  "mcpServers": {
    "engram": {
      "type": "http",
      "url": "https://mcp.getengram.app/mcp"
    }
  }
}

For a client that only speaks stdio, bridge to the remote server with mcp-remote — it drives the same browser OAuth flow, so there is still no key to copy:

{
  "mcpServers": {
    "engram": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.getengram.app/mcp"]
    }
  }
}

(An older version of this README suggested npx @getengram/cli mcp; the CLI has no such command and that configuration never worked.)

How it works

  • Verbatim storage — every message stored exactly as sent, no summarization or compression
  • Semantic search — find relevant context by meaning using bge-base-en-v1.5 embeddings
  • MCP-native — speaks the Model Context Protocol natively, works with any compatible client
  • Multi-tenant — per-organization isolation, team seats, and API key management

Architecture

Runs entirely on Cloudflare's developer platform:

  • Workers — Hono.js API and MCP server
  • D1 — SQLite at the edge for messages and metadata
  • Vectorize — semantic search index
  • Workers AI — embedding generation

Read the full architecture deep-dive.

MCP tools

Engram exposes 6 tools via MCP:

ToolDescription
create_conversationStart a new conversation with optional title, tags, metadata
append_messagesAdd messages to an existing conversation
searchSemantic search across all conversations
get_conversationRetrieve a conversation with its messages
list_conversationsList conversations with filtering and pagination
delete_conversationRemove a conversation and its data

See the API reference for full parameters and examples.

Packages

PackageDescription
apps/mcp-serverCloudflare Worker — MCP server and REST API
apps/cliCLI and MCP bridge (@getengram/cli)
packages/sdkTypeScript SDK (@getengram/sdk)
packages/dbDatabase queries and migrations
packages/sharedShared constants, types, and utilities

Integration guides

Pricing

PlanPriceMessages/month
Free$01,000
Pro$9/mo100,000
Team$27/seat/mo500,000
EnterpriseCustomUnlimited

View pricing

License

Business Source License 1.1 — see LICENSE for details.

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