Offers a suite of tools for CrewAI agents, including semantic search, memory recall, cognitive profiling, and the ability to save and evolve procedural workflows.
Integrates with LangChain via specialized chat message history and retriever components to provide persistent, long-term memory for chains and agents.
Supports importing knowledge bases and personal notes from Obsidian vaults directly into the Mengram memory system to eliminate the cold-start problem for AI agents.
Give your AI agents memory that actually learns
Website · Get API Key · Docs · Console · Examples
pip install mengram-ai # or: npm install mengram-aifrom cloud.client import CloudMemory
m = CloudMemory(api_key="om-...") # Free key → mengram.io
m.add([{"role": "user", "content": "I use Python and deploy to Railway"}])
m.search("tech stack") # → facts
m.episodes(query="deployment") # → events
m.procedures(query="deploy") # → workflows that evolve from failuresWhy Mengram?
Every AI memory tool stores facts. Mengram stores 3 types of memory — and procedures evolve when they fail.
Mengram | Mem0 | Zep | Letta | |
Semantic memory (facts, preferences) | Yes | Yes | Yes | Yes |
Episodic memory (events, decisions) | Yes | No | No | Partial |
Procedural memory (workflows) | Yes | No | No | No |
Procedures evolve from failures | Yes | No | No | No |
Cognitive Profile | Yes | No | No | No |
Multi-user isolation | Yes | Yes | Yes | No |
Knowledge graph | Yes | Yes | Yes | Yes |
LangChain + CrewAI + MCP | Yes | Partial | Partial | Partial |
Import ChatGPT / Obsidian | Yes | No | No | No |
Pricing | Free tier | $19-249/mo | Enterprise | Self-host |
Get Started in 30 Seconds
1. Get a free API key at mengram.io (email or GitHub)
2. Install
pip install mengram-ai3. Use
from cloud.client import CloudMemory
m = CloudMemory(api_key="om-...")
# Add a conversation — auto-extracts facts, events, and workflows
m.add([
{"role": "user", "content": "Deployed to Railway today. Build passed but forgot migrations — DB crashed. Fixed by adding a pre-deploy check."},
])
# Search across all 3 memory types at once
results = m.search_all("deployment issues")
# → {semantic: [...], episodic: [...], procedural: [...]}npm install mengram-aiconst { MengramClient } = require('mengram-ai');
const m = new MengramClient('om-...');
await m.add([{ role: 'user', content: 'Fixed OOM by adding Redis cache layer' }]);
const results = await m.searchAll('database issues');
// → { semantic: [...], episodic: [...], procedural: [...] }# Add memory
curl -X POST https://mengram.io/v1/add \
-H "Authorization: Bearer om-..." \
-H "Content-Type: application/json" \
-d '{"messages": [{"role": "user", "content": "I prefer dark mode and vim keybindings"}]}'
# Search all 3 types
curl -X POST https://mengram.io/v1/search/all \
-H "Authorization: Bearer om-..." \
-d '{"query": "user preferences"}'3 Memory Types
Semantic — facts, preferences, knowledge
m.search("tech stack")
# → ["Uses Python 3.12", "Deploys to Railway", "PostgreSQL with pgvector"]Episodic — events, decisions, outcomes
m.episodes(query="deployment")
# → [{summary: "DB crashed due to missing migrations", outcome: "resolved", date: "2025-05-12"}]Procedural — workflows that evolve
Week 1: "Deploy" → build → push → deploy
↓ FAILURE: forgot migrations
Week 2: "Deploy" v2 → build → run migrations → push → deploy
↓ FAILURE: OOM
Week 3: "Deploy" v3 → build → run migrations → check memory → push → deploy ✅This happens automatically when you report failures:
m.procedure_feedback(proc_id, success=False,
context="OOM error on step 3", failed_at_step=3)
# → Procedure evolves to v3 with new step addedOr fully automatic — just add conversations and Mengram detects failures and evolves procedures:
m.add([{"role": "user", "content": "Deploy failed again — OOM on the build step"}])
# → Episode created → linked to "Deploy" procedure → failure detected → v3 createdCognitive Profile
One API call generates a system prompt from all memories:
profile = m.get_profile()
# → "You are talking to Ali, a developer in Almaty. Uses Python, PostgreSQL,
# and Railway. Recently debugged pgvector deployment. Prefers direct
# communication and practical next steps."Insert into any LLM's system prompt for instant personalization.
Import Existing Data
Kill the cold-start problem:
mengram import chatgpt ~/Downloads/chatgpt-export.zip --cloud # ChatGPT history
mengram import obsidian ~/Documents/MyVault --cloud # Obsidian vault
mengram import files notes/*.md --cloud # Any text/markdownIntegrations
MCP Server — Claude Desktop, Cursor, Windsurf
{
"mcpServers": {
"mengram": {
"command": "mengram",
"args": ["server", "--cloud"],
"env": { "MENGRAM_API_KEY": "om-..." }
}
}
}21 tools for memory management.
LangChain
from integrations.langchain import (
MengramChatMessageHistory,
MengramRetriever,
)
history = MengramChatMessageHistory(
api_key="om-...", user_id="user-1"
)
retriever = MengramRetriever(api_key="om-...")CrewAI
from integrations.crewai import create_mengram_tools
tools = create_mengram_tools(api_key="om-...")
# → 5 tools: search, remember, profile,
# save_workflow, workflow_feedback
agent = Agent(role="Support", tools=tools)OpenClaw
openclaw plugins install openclaw-mengramAuto-recall before every turn, auto-capture after. 12 tools, slash commands, Graph RAG.
Multi-User Isolation
One API key, many users — each sees only their own data:
m.add([...], user_id="alice")
m.add([...], user_id="bob")
m.search_all("preferences", user_id="alice") # Only Alice's memories
m.get_profile(user_id="alice") # Alice's cognitive profileAgent Templates
Clone, set API key, run in 5 minutes:
Template | Stack | What it shows |
Python SDK | Procedures that evolve from deployment failures | |
CrewAI | Agent with 5 memory tools, remembers returning customers | |
LangChain | Cognitive profile + auto-saving chat history |
cd examples/devops-agent && pip install -r requirements.txt
export MENGRAM_API_KEY=om-...
python main.pyAPI Reference
Endpoint | Description |
| Add memories (auto-extracts all 3 types) |
| Semantic search |
| Unified search (semantic + episodic + procedural) |
| Search events and decisions |
| Search workflows |
| Report outcome — triggers evolution |
| Version history + evolution log |
| Cognitive Profile |
| Smart Triggers (reminders, contradictions, patterns) |
| Memory agents (Curator, Connector, Digest) |
| Account info |
Full interactive docs: mengram.io/docs
Community
GitHub Issues — bug reports, feature requests
API Docs — interactive Swagger UI
Examples — ready-to-run agent templates
License
Apache 2.0 — free for commercial use.
Get your free API key · Built by Ali Baizhanov · mengram.io