dakera-mcp

dakera-mcp

Self-hosted MCP-native agent memory server. Gives AI agents persistent, decay-weighted memory via 83 MCP tools — no cloud, full control. RocksDB+HNSW backend. Works with Claude Code, Cursor, and any MCP-compatible agent.

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⚡ dakera-mcp

CI Crate License: MIT Glama

MCP server for Dakera AI. 83 tools. Gives any MCP-compatible AI agent persistent, queryable memory in minutes.

Works with Claude, Claude Code, and any MCP-compatible framework.

Part of Dakera AI — the memory engine for AI agents.

The Dakera memory engine scores 87.6% on LoCoMo (1,540 questions, standard eval) — benchmark details


Run Dakera

The MCP server connects to a Dakera memory server. You need one running first:

docker run -d \
  --name dakera \
  -p 3300:3300 \
  -e DAKERA_ROOT_API_KEY=dk-mykey \
  ghcr.io/dakera-ai/dakera:latest

For persistent storage (recommended):

curl -sSfL https://raw.githubusercontent.com/Dakera-AI/dakera-deploy/main/docker-compose.yml \
  -o docker-compose.yml
DAKERA_API_KEY=dk-mykey docker compose up -d

curl http://localhost:3300/health  # → {"status":"ok"}

Full deployment guide (Docker Compose, Kubernetes, Helm): dakera-deploy


Install

cargo install dakera-mcp

Or with Docker:

docker pull ghcr.io/dakera-ai/dakera-mcp:latest

Connect

Add to .mcp.json (Claude Code) or claude_desktop_config.json (Claude Desktop):

{
  "mcpServers": {
    "dakera": {
      "command": "dakera-mcp",
      "env": {
        "DAKERA_API_URL": "http://localhost:3300",
        "DAKERA_API_KEY": "your-key"
      }
    }
  }
}

What You Get

83 tools across 15 categories:

  • Memory — store, recall, search, decay, importance scoring
  • Sessions — create and manage agent sessions
  • Agents — namespaces, stats, memory health
  • Knowledge — graph construction, entity extraction, clustering, cross-agent network
  • Vectors — upsert, query, hybrid search, batch operations
  • Full-Text — BM25 index, search, stats
  • Operations — health, metrics, backup, audit

Why This Exists

AI agents forget everything when the session ends. Dakera fixes that. This MCP server gives your agent a persistent memory layer with zero infrastructure overhead — point it at a Dakera instance and it works.

dakera.ai for hosted instance
→ Self-host with dakera-deploy

Documentation

Full docs
MCP reference

Related

Repo What it is
dakera-py Python SDK
dakera-js TypeScript SDK
dakera-cli CLI
dakera-deploy Self-host Dakera

Part of the Dakera AI open core. The engine is proprietary. The tools are yours.

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