Dakera MCP server

⚡ dakera-mcp

MCP server for Dakera AI. Gives any MCP-compatible AI agent persistent, queryable memory — with smart token management built in.

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 88.2% Recall@20 on LoCoMo (1,536 evaluated questions · LLM-judged retrieval recall) — benchmark details

Architecture: 14 core tools + on-demand discovery

Starting every agent session with 60+ tool schemas wastes ~15K tokens before you write a single message. dakera-mcp solves this with hybrid tool exposure:

• 14 tools loaded by default — the 12 highest-frequency memory operations + 2 meta-discovery tools
• On-demand expansion — use dakeradiscovertools and dakeraloadtools to fetch additional tool schemas only when you need them

Default tool set (core profile)

Profiles & token cost

Accessing additional tools

# In your agent: discover what's available
dakera_discover_tools(tier="power")
→ returns names + descriptions, no schemas loaded

# Load schemas for the tools you want
dakera_load_tools(tools=["dakera_consolidate", "dakera_agent_stats"])
→ returns full inputSchema for each tool

Profile selection

The profile controls which tools appear in tools/list. Three ways to set it:

1. Per-request (in tools/list params):

{"profile": "power"}

2. Environment variable (applies to all requests):

DAKERA_MCP_PROFILE=power

Shortened. The full README is on GitHub.