mengram-ai 2.3.0

AI memory layer with autonomous agents. Open-source Mem0 alternative with memory agents, webhooks, and cognitive insights.

🧠 Mengram — AI Memory Layer with Autonomous Agents

Open-source memory layer for AI apps. Not just storage — Mengram has autonomous agents that clean, analyze, and find hidden patterns in your knowledge.

Website · Dashboard · API Docs · PyPI

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Why Mengram?

	Mengram	Mem0
Memory Storage	✅	✅
Semantic Search	✅	✅
Knowledge Graph	✅	✅
Autonomous Agents	✅ Curator, Connector, Digest	❌
Team Shared Memory	✅ Invite codes, privacy controls	❌
AI Reflections	✅ Patterns, insights, behavioral analysis	❌
Webhooks	✅	✅
MCP Server	✅ Claude Desktop, Cursor, Windsurf	❌
Self-hostable	✅	✅
Price	Free	$19-249/mo

Quick Start (60 seconds)

1. Get API key

Sign up at mengram.io — free, no credit card.

2. Install

pip install mengram-ai

3. Connect to Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "mengram": {
      "command": "mengram",
      "args": ["server", "--cloud"],
      "env": {
        "MENGRAM_API_KEY": "your-key-here"
      }
    }
  }
}

Done. Claude now has persistent memory.

Python SDK

from mengram.cloud.client import CloudMemory

m = CloudMemory(api_key="om-...")

# Add memories from conversation
m.add([
    {"role": "user", "content": "I deployed Mengram on Railway with PostgreSQL 15"},
    {"role": "assistant", "content": "Great, noted the deployment setup."}
], user_id="ali")

# Semantic search
results = m.search("deployment setup", user_id="ali")

# Run memory agents
m.run_agents(agent="all", auto_fix=True)

# Get AI insights
insights = m.insights()

# Team memory
team = m.create_team("Backend Team")
m.share_memory("Redis", team_id=team["id"])

# Webhooks
m.create_webhook(url="https://hooks.slack.com/...", name="Slack")

Memory Agents

Three autonomous agents that analyze your memory:

🧹 Curator — Finds contradictions, stale facts, duplicates. Auto-cleans with auto_fix=True. Reports memory health score.

🔗 Connector — Discovers hidden connections, behavioral patterns, skill clusters. Gives strategic suggestions with priorities.

📰 Digest — Weekly summary with headlines, trends, focus areas, and recommendations.

curl -X POST "https://mengram.io/v1/agents/run?agent=all&auto_fix=true" \
  -H "Authorization: Bearer YOUR_KEY"

Team Shared Memory

Share knowledge across your team. Create → invite → share:

# Create team → get invite code
POST /v1/teams {"name": "Backend Team"}

# Colleague joins with code
POST /v1/teams/join {"invite_code": "xK9m2Qw5ab"}

# Share an entity
POST /v1/teams/3/share {"entity": "Redis"}

Search automatically includes shared team knowledge.

Webhooks

m.create_webhook(
    url="https://webhook.site/your-id",
    event_types=["memory_add", "memory_update", "memory_delete"],
    secret="optional-hmac-secret"
)

API Endpoints

Endpoint	Description
POST /v1/add	Add memories from conversation
POST /v1/search	Semantic search
POST /v1/agents/run	Run memory agents
GET /v1/insights	AI-generated insights
POST /v1/teams	Create team
POST /v1/teams/join	Join team
POST /v1/webhooks	Create webhook
GET /v1/graph	Knowledge graph
GET /v1/timeline	Temporal search
GET /v1/stats	Usage statistics

Full docs: https://mengram.io/docs

Architecture

┌──────────────────────────────────────┐
│          Your AI Clients             │
│  Claude Desktop · Cursor · Windsurf  │
└──────────────┬───────────────────────┘
               │ MCP / REST API
┌──────────────▼───────────────────────┐
│        Mengram Cloud API             │
│  Extraction · Re-ranking · Search    │
├──────────────────────────────────────┤
│       Memory Agents Layer            │
│  🧹 Curator · 🔗 Connector · 📰 Digest│
├──────────────────────────────────────┤
│       Storage Layer                  │
│  PostgreSQL · pgvector · Teams       │
│  Webhooks · Reflections · Graph      │
└──────────────────────────────────────┘

License

MIT

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Built by Ali Baizhanov