Claude Desktop Integration

Give Claude Desktop persistent memory that survives across conversations. Dakera's MCP server connects directly — Claude remembers your preferences, project context, and past interactions without re-explaining every session.

Quick Start

docker run -d --name dakera \
  -p 3000:3000 \
  -e DAKERA_API_KEY=dk-your-key-here \
  -v dakera-data:/data \
  ghcr.io/dakera-ai/dakera:latest

{
  "mcpServers": {
    "dakera": {
      "command": "docker",
      "args": ["run", "--rm", "-i",
        "--network", "host",
        "ghcr.io/dakera-ai/dakera-mcp:latest"],
      "env": {
        "DAKERA_API_URL": "http://localhost:3000",
        "DAKERA_API_KEY": "dk-your-key-here",
        "DAKERA_AGENT_ID": "claude-desktop",
        "DAKERA_MCP_PROFILE": "core"
      }
    }
  }
}

What Claude Can Do with Memory

Example Interactions

Personal Preferences

Claude automatically stores preferences you mention:

You: "I prefer TypeScript over JavaScript and always use strict mode"
Claude: [stores with importance 0.8, tags: preferences, coding]

// Next session:
You: "Help me set up a new project"
Claude: [recalls preference] "I'll set this up with TypeScript in strict mode,
since that's your preference."

Project Context

You: "We're building a SaaS with Next.js, Prisma, and Stripe"
Claude: [stores project architecture context]

// Days later:
You: "Add a webhook handler for subscription changes"
Claude: [recalls Stripe + Next.js context] "I'll create a Next.js API route
at /api/webhooks/stripe that handles subscription.updated events using
your Prisma schema..."

Research & Notes

You: "I've been researching RAG approaches. Key finding: hybrid retrieval
     outperforms pure vector by 15-20% on factual recall tasks."
Claude: [stores as high-importance research finding]

// Later:
You: "Should we use pure vector search for our docs chatbot?"
Claude: [recalls research] "Based on your earlier research, hybrid retrieval
outperforms pure vector by 15-20% on factual recall. I'd recommend combining
vector with BM25..."

Privacy & Data Control

• Self-hosted: All memory data stays on your machine or server. Nothing leaves your infrastructure.
• Encrypted: AES-256-GCM encryption at rest. Even if someone accesses the data files, they can't read your memories.
• You own the data: Export, backup, or delete any time. No lock-in.
• Per-namespace control: Create separate namespaces for work, personal, or different projects.

Configuration Options

Profile Selection (DAKERA_MCP_PROFILE)

The DAKERA_MCP_PROFILE environment variable controls which tools appear when Claude lists available tools. Profiles let you balance capability vs. context window usage:

# Set in your claude_desktop_config.json env block:
"DAKERA_MCP_PROFILE": "power"    # Options: core, power, admin, all

Next Steps

• Full MCP Server documentation — all 14 core tools (86+ available via profiles) explained
• Quick Start guide — detailed server setup
• Cursor integration — same memory for AI coding
• Memory Patterns — common use cases and architectures

Frequently Asked Questions

Further reading: MCP Protocol Explained · Dakera MCP: Real-World Use Cases · MCP Memory Server Setup Guide