io.github.tstockham96/engram
Quality Score
78
/100
Intelligent agent memory with automatic extraction, consolidation, and bi-temporal recall.
§01 Install
Claude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"engram": {
"command": "npx",
"args": [
"-y",
"engram-sdk"
],
"env": {
"GEMINI_API_KEY": "<your-gemini_api_key>"
}
}
}
}Cursor (.cursor/mcp.json)
{
"mcpServers": {
"engram": {
"command": "npx",
"args": [
"-y",
"engram-sdk"
],
"env": {
"GEMINI_API_KEY": "<your-gemini_api_key>"
}
}
}
}Cline (cline_mcp_settings.json)
npx -y engram-sdk§02 Environment variables
GEMINI_API_KEYrequiredsecret
Google Gemini API key for embeddings and LLM operations
§03 MCP Quality Score · methodology
freshness
23
completeness
10
installability
25
documentation
15
stability
5
§04 Alternatives in Memory & RAG
DoneThat
ai.donethat/donethat
Privacy-first work tracking with summaries, reports, coaching, and AI-ready long-term memory.
Fodda Knowledge Graphs
ai.fodda/mcp-server
Expert-curated knowledge graphs for AI agents — PSFK Retail, Beauty, Sports and more.
ai.meminal/meminal
ai.meminal/meminal
Memory for deep conversational context across any platform