Mengram
FreemiumPersistent memory layer for AI agents — semantic, episodic, procedural.
By Tanmay Verma, Founder · Last verified 06 Jul 2026
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Added 6d ago
77/100Safe BetIn short
Mengram — Persistent memory layer for AI agents — semantic, episodic, procedural. Best for Developers building personal AI assistants that need persistent context across sessions, Teams creating multi-agent systems requiring shared memory between agents, SaaS builders needing per-user memory scoping for end-user personalization. Free to start; paid plans from $5/mo.
Is Mengram actually worth it?
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Editorial Verdict
Best for
Developers building personal AI assistants that need persistent context across sessionsTeams creating multi-agent systems requiring shared memory between agentsSaaS builders needing per-user memory scoping for end-user personalizationAI tinkerers wanting persistent context across tools (Claude, Cursor, OpenAI)Startups seeking an open-source memory layer with self-hosting option
Not ideal for
Enterprises needing SOC 2 or HIPAA compliance (not offered)Non-technical users who don't work with APIs or MCPTeams requiring fully offline-only memory (cloud API dependent)Projects that need a simple memory solution without structured typesUsers who prefer a fully managed service with no self-hosting complexity
Mengram delivers on its promise: persistent memory that works across multiple AI tools. The open-source ethos, multilingual support, and procedure evolution are genuine differentiators. It's not for anyone afraid of APIs or needing compliance certifications, but for developers who want memory without a RAG project, it's a compelling $5/month option.
Last verified: July 2026
What's new in Mengram
Checked 3 days agoAcross the latest 9 updates: 8 feature updates and 1 launch.
FeatureBlog·May 6Newest
5 Patterns We See in Production AI Agent Memory
Five real-world AI memory patterns from production agents: Daily Briefs, multi-tenant SaaS, knowledge work, etc., with architecture for each.
LaunchBlog·May 4
Add Memory to OpenAI Agent Builder in 2 Minutes via OpenAPI
OpenAPI integration adds persistent memory to OpenAI Agent Builder with auth, multi-user scoping, and three tool calls.
FeatureBlog·May 4
Multilingual AI Memory: Retrieval in 23 Languages
Mengram uses Cohere multilingual-v3 to fix English-biased retrieval; demonstrates native multilingual support beyond query translation.
FeatureBlog·Apr 22
Multi-Tenant MCP Servers with user_id Isolation
One-argument fix adds user_id isolation to MCP servers for multi-tenant SaaS without breaking backward compatibility.
FeatureBlog·Apr 9
Add Persistent Memory to Claude Managed Agents via MCP
Two-minute MCP setup gives Claude Managed Agents long-term memory: remembers users, learns from failures, builds cognitive profiles.
FeatureBlog·Apr 1
Context Engineering: Why Memory Is the Missing Piece
Guide on context engineering replacing prompt engineering; highlights persistent memory as the hardest pillar for agents.
FeatureBlog·Mar 18
How to Add Persistent Memory to Cursor AI (MCP Setup)
Step-by-step MCP setup for Cursor AI to remember codebase, preferences, and decisions across sessions.
FeatureBlog·Mar 10
Build AI Agents That Learn From Experience (Persistent Memory Pattern)
Memory loop pattern for autonomous agents: store outcomes, recall before decisions, evolve procedures from failures, with Python examples.
FeatureBlog·Mar 5
Add Persistent Memory to Claude Code (Auto-Save, Auto-Recall, Profile)
One-command setup gives Claude Code persistent memory: auto-saves conversations, auto-recalls context, loads cognitive profile.
What independent users actually report about Mengram
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
34 mentions across 5 sources (Hacker News, YouTube, Product Hunt, GitHub, Lemmy).
56% positive44% critical
Recurring strengths
- +Three memory types (semantic, episodic, procedural) are more human-like than flat vectors.
- +Cognitive Profile generation makes personalization easy with one API call.
- +Low latency (<50ms) for memory operations, as claimed in documentation.
- +Multilingual support with 23 languages via Cohere embeddings is a standout feature.
- +MCP server with 30 tools integrates directly into Claude Code and Cursor.
Recurring frustrations
- −MCP server returns Cloudflare 403 error for some users, breaking core functionality.
- −Self-hosting documentation is unclear; version mismatches reported.
- −Hard edge cases like contradictions and staleness lack built-in resolution.
- −Very small community (183 stars, 20 issues) means limited support resources.
- −LangChain integration example code was requested but not immediately available.
Patterns worth knowing
Three-memory-type architecture is a genuine improvement over flat vector stores
Seen on Hacker News, Product Hunt, Lemmy
Self-hosting and deployment instructions need improvement
Seen on GitHub
MCP server reliability issues with Cloudflare blocking
Seen on GitHub
Learning curve
intermediateProductive in ~A few hours
Hidden costs people mention
- • Free tier is limited to 40 memory adds/month — likely too small for serious use.
- • Self-hosting requires own infrastructure; official docs may lack clarity on API key usage.
Viability Score
77/100
Safe BetHow likely is Mengram to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
momentum
55
funding runway
80
website health
90
wrapper dependency
100
Last calculated: July 2026
How we score →Key Features
- Three memory types: semantic, episodic, procedural
- Cognitive Profile generation from all memories
- Multilingual support across 23 languages (Cohere embeddings)
- MCP server with 30 tools for Claude/Cursor/Windsurf
- Python and JavaScript SDKs
- LangChain Retriever integration
- CrewAI persistent memory support
- OpenClaw plugin (12 tools)
- n8n workflow template
- Self-hosting option (Apache 2.0)
- Webhook notifications for memory events
- CLI for setup, import, and rules
- Multi-tenant user_id isolation
- Auto-save and auto-recall hooks for Claude Code
- Procedure evolution from failures
About Mengram
FreemiumIntermediateAPI availableWeb · API · Plugin · CLI
Mengram is an open-source memory layer that gives AI agents persistent, human-like memory across conversations, tools, and devices. It extracts three memory types—semantic (facts, preferences), episodic (events, decisions), and procedural (workflows, habits)—from user interactions and stores them in a single API. One call returns a Cognitive Profile, a ready-to-use system prompt that personalizes any AI (ChatGPT, Claude, Cursor, etc.) without RAG pipelines or vector database setup. Mengram targets developers building personal AI assistants, multi-agent systems, or SaaS apps that need to remember users across sessions. It integrates via MCP server (30 tools), Python/JS SDKs, LangChain, CrewAI, OpenClaw, and n8n. The free tier (40 memory adds/month) requires no credit card; paid plans start at $5/month for personal projects. Key features include multilingual support using Cohere's multilingual embeddings (23 languages), low latency (<50ms), and procedure evolution from failures—workflows that auto-improve. Mengram also offers Knowledge Graph (entities, relations), Smart Triggers (contradiction alerts, reminders), and Memory Agents (Curator, Connector, Digest). It is self-hostable under Apache 2.0, avoiding vendor lock-in. What sets Mengram apart is its structured memory that mirrors human cognition—not just raw vector storage. Compared to Mem0 or Supermemory, Mengram adds procedural memory, cross-lingual retrieval, and built-in Knowledge Graph. It's a solid pick for developers who want persistent context without building a RAG pipeline.
Behind the Verdict
We've seen a lot of 'memory' tools that are just vector stores with a coat of paint. Mengram is different—it actually structures memory into semantic, episodic, and procedural types, mirroring how humans recall. That procedural memory piece is the killer feature: workflows that evolve from failures and successes. In practice, this means your Claude Code session remembers not just facts but also the steps it took to fix a bug last week, then adapts them. The MCP server with 30 tools is a no-brainer for anyone using Claude Desktop or Cursor—setup takes two commands. The free tier is generous enough to test seriously. Where it bites: the free tier limits to 40 memory adds/month, which disappears fast in active use. And if you need SOC 2 or HIPAA, don't look here—self-hosting gives you control, but compliance certs aren't on the roadmap yet. Compared to Mem0, Mengram wins on structured memory and multilingual support; Mem0 is simpler but less capable. For voice agent memory via Vapi, Mengram's integration is ahead. Our take: if you're building an AI that needs to 'get' a user over time—personal assistant, coding agent, SaaS personalization—start here. If you just need a chunk-based RAG, stick with a simpler tool.
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Use Cases
- Give your AI assistant persistent memory of user preferences and project context across sessions.
- Enable multi-agent crews to share and recall past decisions and workflows automatically.
- Add per-user memory scoping to SaaS apps so each customer's agent remembers their distinct data.
- Automate daily briefs that evolve based on recurring events and procedural learning.
- Replace complex RAG pipelines with a single API call for personalized AI responses.
- Build voice assistants that remember user facts and conversation history across calls.
Models Under the Hood
Cohere multilingual-v3
Limitations
- The free tier is very limited (40 adds/month, 200 searches/month, 3 sub-users, 20 req/min).
- Procedure evolution and smart triggers are gated behind paid plans.
- Self-hosting requires infrastructure; cloud API latency may vary.
- No native mobile or desktop apps.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Integrations
Resources & Guides
Frequently Asked Questions
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