Blog/CAS vs Mem0: Choosing the Right Memory System for Your AI Agent

CAS vs Mem0: Choosing the Right Memory System for Your AI Agent

Both CAS and Mem0 solve the same fundamental problem: LLMs don't remember. Every conversation starts fresh. Context from yesterday's session is gone.

C
CAS Team
December 1, 202410 min read

CAS vs Mem0: Choosing the Right Memory System for Your AI Agent

Both CAS and Mem0 solve the same fundamental problem: LLMs don't remember. Every conversation starts fresh. Context from yesterday's session is gone.

But these systems take fundamentally different approaches. Understanding the differences will help you choose the right solution for your use case.

Mem0 is a universal memory layer for any AI application—chat assistants, customer support bots, autonomous agents. CAS is purpose-built for AI-assisted software development with Claude Code, combining memory with task tracking, rules, and skills.

The Core Problem

AI models are stateless. Claude, GPT-4, and other LLMs process each request independently. They don't remember:

  • What you discussed yesterday
  • Your coding preferences
  • Project conventions you've explained
  • Decisions you've made together
  • Patterns you've established

This forces developers into repetitive cycles of re-explaining context with every new session.

Both CAS and Mem0 address this. But they do it differently.

---

Mem0: Universal Memory Infrastructure

Mem0 (pronounced "mem zero") positions itself as the "memory passport" for AI—a universal layer that travels with you across apps and agents.

How Mem0 Works

Mem0 provides an API that any AI application can integrate:

``python

from mem0 import MemoryClient

client = MemoryClient(api_key="your-key")

Store a memory

client.add("User prefers TypeScript over JavaScript", user_id="user123")

Retrieve relevant memories

memories = client.search("What programming language does user prefer?", user_id="user123")

`

When you interact with an AI, Mem0:

  • Captures relevant information from the conversation
  • Compresses and indexes it semantically
  • Stores it with user/session context
  • Retrieves relevant memories for future conversations

Key Mem0 Features

| Feature | Description |

|---------|-------------|

| Memory Compression | Converts conversations into optimized memory representations |

| Semantic Search | Finds relevant memories based on meaning, not just keywords |

| Graph Memory | Builds relationship networks between memories |

| Dynamic Decay | Gradually forgets low-relevance information |

| Cross-Platform | Works with any LLM: OpenAI, Claude, local models |

| Cloud or Self-Hosted | Run on Mem0's cloud or your own infrastructure |

Mem0 Pricing

| Tier | Price | Memories | Use Case |

|------|-------|----------|----------|

| Hobby | Free | 10K | Testing and prototyping |

| Starter | $19/month | 50K | Small applications |

| Pro | $249/month | Unlimited | Production apps |

| Enterprise | Custom | Unlimited | Large scale, compliance |

Best For

Mem0 excels when you need:

  • Memory for customer-facing chatbots
  • Personalization across multiple applications
  • A general-purpose memory API for any AI system
  • Framework-agnostic memory that works with any LLM

---

CAS: Purpose-Built for Coding Agents

CAS (Coding Agent System) takes a different approach. Rather than being a universal memory layer, it's specifically designed for AI-assisted software development with Claude Code.

How CAS Works

CAS runs as an MCP server that integrates directly with Claude Code:

`bash

Add CAS to Claude Code

claude mcp add cas

`

Once connected, CAS provides context-aware memory and more:

`

Store a learning

cas_remember: "This project uses React Query for server state, not Redux"

Search across all context

cas_search: "How did we handle authentication?"

Create a tracked task

cas_task_create: "Implement user authentication"

`

Key CAS Features

| Feature | Description |

|---------|-------------|

| Unified Context | Memories, tasks, rules, and skills in one system |

| Task Tracking | Track work with full context restoration |

| Coding Rules | Persistent coding standards that surface automatically |

| Skills | Learned procedures and workflows |

| Semantic Search | Hybrid BM25 + vector search across all content |

| Claude Code Native | Deep integration with Claude Code workflows |

What Makes CAS Different

CAS isn't just memory—it's a complete context engineering system:

Tasks with Context: `

cas_task_create: "Fix authentication bug"

cas_task_start: "cas-abc1"

... work on the task ...

cas_task_notes: "Found issue in JWT validation"

cas_task_close: "Fixed by adding expiry check"

`

When you resume a task, its full context restores automatically.

Rules that Persist: `

cas_rule_create: "Always use async/await instead of .then() chains"

`

Rules surface when relevant—they don't consume tokens when you're not working on related code.

Skills that Learn: `

cas_skill_create: "Run our test suite: bun test --coverage"

`

Skills capture patterns that become available for future sessions.

CAS Pricing

CAS runs locally with a generous free tier. No data leaves your machine.

| Aspect | CAS |

|--------|-----|

| Cost | Free tier available |

| Data Location | Local (your machine) |

| Privacy | Complete—no external calls |

| Dependencies | MCP server, local storage |

---

Feature Comparison

| Capability | CAS | Mem0 |

|------------|-----|------|

| Memory Storage | ✅ Local | ✅ Cloud/Self-hosted |

| Semantic Search | ✅ Hybrid BM25+Vector | ✅ Vector-based |

| Task Tracking | ✅ Full system | ❌ Not included |

| Coding Rules | ✅ With auto-surfacing | ❌ Not included |

| Skills/Procedures | ✅ Captured and reusable | ❌ Not included |

| Claude Code Integration | ✅ Native MCP | ⚠️ Via MCP adapter |

| Framework Support | Claude Code only | Any LLM framework |

| Privacy | ✅ Fully local | ⚠️ Cloud by default |

| Graph Relationships | ✅ Task dependencies | ✅ Memory graph |

| Cost | Free | From $0-249+/month |

---

Use Case Comparison

Building a Coding Assistant

Choose CAS if:
  • You're using Claude Code for development
  • You need task tracking alongside memory
  • You want coding rules to apply automatically
  • You prefer local-first, private data
  • You need deep integration with developer workflows
Choose Mem0 if:
  • You're building a custom coding assistant from scratch
  • You need to integrate with multiple LLM providers
  • You want cloud-hosted memory management
  • Your assistant serves multiple users at scale

Building a Customer Support Bot

Choose Mem0. CAS is specifically designed for development workflows. Mem0's user-centric memory model and framework-agnostic API make it ideal for customer-facing applications.

Building a Multi-Agent System

| Requirement | Recommendation |

|-------------|----------------|

| Coding-focused agents | CAS for Claude Code agents |

| General-purpose agents | Mem0 for universal memory |

| Mixed workloads | Consider using both |

---

Integration Patterns

Using CAS with Claude Code

CAS integrates natively as an MCP server:

`json

{

"mcpServers": {

"cas": {

"command": "cas-mcp-server"

}

}

}

`

All CAS tools are immediately available:

  • cas_remember — Store memories
  • cas_search — Find relevant context
  • cas_task_create — Track tasks
  • cas_task_start / cas_task_close — Manage work
  • cas_rules_list — View active rules
  • cas_skill_list — Available skills

Using Mem0 with Claude Code

Mem0 can integrate via its OpenMemory MCP server:

`json

{

"mcpServers": {

"mem0": {

"command": "npx",

"args": ["-y", "@mem0/mcp-server"],

"env": {

"MEM0_API_KEY": "your-api-key"

}

}

}

}

`

This provides:

  • add_memories — Store information
  • search_memory — Retrieve relevant context
  • list_memories — View all memories
  • delete_all_memories — Clear memory

---

Performance Comparison

Mem0 Benchmarks

According to Mem0's published research:

  • 26% accuracy improvement over OpenAI Memory
  • 91% lower p95 latency than full-context approaches
  • 90% token savings compared to sending full conversation history

CAS Approach

CAS takes a different approach to performance:

  • Local-first: No network latency for memory operations
  • Hybrid search: BM25 + semantic for balanced retrieval
  • Context budgeting: Automatic token management
  • Selective surfacing: Rules and context only when relevant

---

Privacy and Data Control

Mem0

| Deployment | Data Location |

|------------|---------------|

| Cloud (default) | Mem0's infrastructure |

| Self-hosted | Your infrastructure |

| Air-gapped | Private cloud/on-prem |

Mem0 is SOC 2 and HIPAA compliant with BYOK (Bring Your Own Key) support.

CAS

| Deployment | Data Location |

|------------|---------------|

| Default | Local filesystem |

| Only option | Your machine |

CAS runs entirely locally. No data leaves your machine. No API keys required for memory operations.

If data privacy is paramount and you're using Claude Code, CAS offers complete data sovereignty with zero external dependencies.

---

When to Use Each

Choose CAS When:

  • You use Claude Code — Native integration, no adapters needed
  • Development is your focus — Task tracking, rules, skills are valuable
  • Privacy matters — Everything stays local
  • You want free — No usage costs, no API limits
  • You need task context — Resume work exactly where you left off

Choose Mem0 When:

  • Building for multiple LLMs — Framework-agnostic API
  • Customer-facing apps — User-centric memory model
  • Cloud infrastructure — Managed memory service
  • Multiple users — Per-user memory isolation
  • Enterprise compliance — SOC 2, HIPAA, audit trails

Consider Using Both:

Some workflows benefit from both systems:

  • CAS for development work with Claude Code
  • Mem0 for customer-facing features you're building

They solve different problems and can coexist.

---

Migration Considerations

From Nothing to CAS

  • Install CAS MCP server
  • Add to Claude Code configuration
  • Start using cas_remember for important context
  • Gradually add tasks, rules, and skills

From Nothing to Mem0

  • Sign up for Mem0 account
  • Integrate SDK into your application
  • Add memory calls at appropriate points
  • Configure user/session isolation

From Mem0 to CAS (for Claude Code users)

If you're using Mem0 primarily for Claude Code development:

  • Export important memories from Mem0
  • Set up CAS MCP server
  • Re-add key context with cas_remember
  • Add task tracking for active work
  • Create rules for recurring patterns

---

Conclusion

Mem0 and CAS serve different niches in the AI memory landscape:

Mem0 is a powerful, universal memory infrastructure. It's ideal for building memory into any AI application, especially customer-facing products that need personalization across users and sessions. CAS is purpose-built for AI-assisted software development. It combines memory with task tracking, coding rules, and skills—creating a complete context engineering system for Claude Code users.

For developers using Claude Code as their primary AI assistant, CAS offers deeper integration, richer context management, and complete privacy—all at no cost.

For teams building AI products that need memory, Mem0 provides proven infrastructure with enterprise features and scale.

The right choice depends on your use case. Often, the answer is clear based on whether you're using an AI assistant (CAS) or building AI products (Mem0).

If you're a Claude Code user, try CAS today. It's free, local, and purpose-built for your workflow. Start with cas_remember` and discover how persistent context transforms your development experience.

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