yantrikdb-server

Overview

YantrikDB is a unique cognitive memory engine that manages memories rather than just storing them. Unlike traditional vector databases, it implements three key features: forgetting (via temporal decay with configurable half-life), consolidation (collapsing similar memories into canonical forms), and conflict detection (identifying contradictions between memories). It offers significant token savings compared to file-based memory systems - up to 99.9% at 5,000 memories while improving recall precision. The system can be deployed as a library, HTTP server, or MCP server, with proactive triggers that surface what needs attention rather than requiring agents to constantly query.

Try asking AI

After installing, here are 7 things you can ask your AI assistant:

• remember

  Store new memories with text, importance, and temporal decay

  Try:Remember that the CEO is AliceTry:Record the meeting decision with high importance
• recall

  Retrieve relevant memories based on query and context

  Try:Who leads the engineering team?Try:What decisions were made in the last meeting
• forget

  Remove specific memories from the database

  Try:Forget the old project deadlineTry:Remove outdated information about the product launch
• correct

  Update or correct existing memories

  Try:Correct the team leader's name to BobTry:Update the project deadline to next Friday
• think

  Perform cognitive operations: consolidate memories, detect contradictions

  Try:Think through all stored memories for conflictsTry:Consolidate similar memories about the client project
• memory

  Access or manipulate memory structures

  Try:Show all memories about the Q3 planningTry:List all memories marked as high importance
• trigger

  Get proactive insights from memory system

  Try:What needs attention right now?Try:Show me any conflicts in my memories
• graph

  Access the knowledge graph of entities and relationships

  Try:Show me all relationships involving AliceTry:What entities are connected to the project
• category

  Organize or query memories by categories

  Try:Show me all memories in the 'development' categoryTry:Categorize these new memories about client feedback
• conflict

  List or resolve contradictions in stored memories

  Try:List all conflicts in my memoriesTry:Resolve the contradiction about the deadline
• session

  Manage session-specific memories and context

  Try:Start a new session for the client projectTry:Recall what we discussed in the last session
• temporal

  Query memories based on time: stale, upcoming, or time-bound

  Try:What memories are becoming stale?Try:Show me any approaching deadlines

Comparable tools

Installation

pip install yantrikdb-mcp

{
  "mcpServers": {
    "yantrikdb": {
      "command": "yantrikdb-mcp"
    }
  }
}

{
  "mcpServers": {
    "yantrikdb": {
      "command": "yantrikdb-mcp",
      "env": {
        "YANTRIKDB_SERVER_URL": "http://node1:7438,http://node2:7438",
        "YANTRIKDB_TOKEN": "ydb_your_database_token"
      }
    }
  }
}

docker run -p 7438:7438 ghcr.io/yantrikos/yantrikdb:latest

FAQ

How does YantrikDB differ from vector databases like Pinecone or Weaviate?

Vector databases focus on nearest-neighbor lookup but lack memory management features. YantrikDB implements temporal decay, consolidation of similar memories, and conflict detection - making it a cognitive memory system rather than just a storage layer.

Can I use YantrikDB without an internet connection?

Yes, YantrikDB can run as an embedded library that works offline with a local SQLite file. It only requires network connectivity if you use the clustered deployment option.

How much memory does YantrikDB use at scale?

Despite storing thousands of memories, YantrikDB maintains a constant ~70 tokens per query, regardless of memory count. This contrasts with file-based systems that grow linearly with memory count.

On Hacker News

Recent discussion from the developer community.

• Show HN: A memory database that forgets, consolidates, and detects contradiction▲ 48💬 33
  Story by pranabsarkar · 2026-04-14

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