Server data from the Official MCP Registry
Persistent memory for AI agents — verbatim conversations, searchable by meaning.
About
Persistent memory for AI agents — verbatim conversations, searchable by meaning.
Remote endpoints: streamable-http: https://mcp.getengram.app/mcp
Security Report
Valid MCP server (1 strong, 1 medium validity signals). 2 known CVEs in dependencies Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 3 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-debragail-engram": {
"url": "https://mcp.getengram.app/mcp"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Engram
Memory infrastructure for AI agents. Store every conversation verbatim. Search by meaning.
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
- Sign up at getengram.app and get your API key
- Add to your MCP config (Claude Desktop, Claude Code, Cursor, etc.):
{
"mcpServers": {
"engram": {
"command": "npx",
"args": ["-y", "@getengram/cli@latest", "mcp"],
"env": {
"ENGRAM_API_KEY": "engram_sk_live_..."
}
}
}
}
- Start using it. Your agent now has persistent memory.
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:
| Tool | Description |
|---|---|
create_conversation | Start a new conversation with optional title, tags, metadata |
append_messages | Add messages to an existing conversation |
search | Semantic search across all conversations |
get_conversation | Retrieve a conversation with its messages |
list_conversations | List conversations with filtering and pagination |
delete_conversation | Remove a conversation and its data |
See the API reference for full parameters and examples.
Packages
| Package | Description |
|---|---|
apps/mcp-server | Cloudflare Worker — MCP server and REST API |
apps/cli | CLI and MCP bridge (@getengram/cli) |
packages/sdk | TypeScript SDK (@getengram/sdk) |
packages/db | Database queries and migrations |
packages/shared | Shared constants, types, and utilities |
Integration guides
Pricing
| Plan | Price | Messages/month |
|---|---|---|
| Free | $0 | 1,000 |
| Pro | $9/mo | 100,000 |
| Team | $27/seat/mo | 500,000 |
| Enterprise | Custom | Unlimited |
Links
- Website: getengram.app
- Documentation: getengram.app/docs
- Blog: getengram.app/blog
- npm: @getengram/cli
License
Business Source License 1.1 — see LICENSE for details.
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