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yantrikdb

Cognitive memory engine for AI agents — temporal decay, contradiction detection, autonomous consolidation, knowledge graph, ANN recall via HNSW. Embeddable Rust library with Python bindings; powers yantrikdb-server (HTTP gateway, MCP server, openraft cluster). AGPL.

Preview status · 2026-05-16

What is yantrikdb?

01

Quick decision

Use this section to decide whether the project is worth a deeper read.
Best forUsers who want source-backed project understanding before installing it.

Match the project to your task before installing it.

Capabilitymcp_config, recipe, host_instruction, eval, preflight

Cognitive memory engine for AI agents — temporal decay, contradiction detection, autonomous consolidation, knowledge graph, ANN recall via HNSW. Embeddable Rust library with Python bindings; powers yantrikdb-server (HTTP gateway, MCP server, openraft cluster). AGPL.

Repositoryyantrikos/yantrikdb

17 stars · 6 forks

02

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.
1

Overview

Related topics: Five-Index Architecture, Core API Reference, Installation

Sources: [crates/yantrikdb-core/src/cognition/state.rs:1-50]()
2

Installation

Related topics: Overview, Python Bindings, MCP Server Integration

Source: https://github.com/yantrikos/yantrikdb / Human Manual
3

Five-Index Architecture

Related topics: Decoupled Write Path (LSM Architecture), Storage Engine, Core API Reference

Sources: [crates/yantrikdb-core/src/engine/indices.rs:1-50]()
4

Decoupled Write Path (LSM Architecture)

Related topics: Five-Index Architecture, Storage Engine

Sources: [CONCURRENCY.md]()
5

Storage Engine

Related topics: Five-Index Architecture, Decoupled Write Path (LSM Architecture)

Sources: [engine/lifecycle.rs:200-225]()

Sources: https://github.com/yantrikos/yantrikdb, Human Manual, Project Pack evidence, and downstream validation signals.

03

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.
Stars17 stars
Forks6 forks
Contributors2 contributors
Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using yantrikdb with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

04

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.
1

Try the prompt first

Test the workflow without installing the upstream project.

preview
2

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual
3

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context
4

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify
pip install yantrikdb-mcp

Official start command · https://github.com/yantrikos/yantrikdb#readme · verified: yes

05

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

yantrikdb Manual

Related topics: Five-Index Architecture, Core API Reference, Installation

Open the full manual
  1. yantrikdb Human Manual
  2. Table of Contents
  3. Overview
  4. Related Pages
  5. Architecture Overview
  6. Core Modules
  7. Cognitive Node Model
  8. Node Kinds
1

Overview

Related topics: Five-Index Architecture, Core API Reference, Installation

Sources: [crates/yantrikdb-core/src/cognition/state.rs:1-50]()
2

Installation

Related topics: Overview, Python Bindings, MCP Server Integration

Source: https://github.com/yantrikos/yantrikdb / Human Manual
3

Five-Index Architecture

Related topics: Decoupled Write Path (LSM Architecture), Storage Engine, Core API Reference

Sources: [crates/yantrikdb-core/src/engine/indices.rs:1-50]()
4

Decoupled Write Path (LSM Architecture)

Related topics: Five-Index Architecture, Storage Engine

Sources: [CONCURRENCY.md]()
5

Storage Engine

Related topics: Five-Index Architecture, Decoupled Write Path (LSM Architecture)

Sources: [engine/lifecycle.rs:200-225]()

06

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

07

Preflight checks

Treat this preview as a planning asset, not proof that your local environment is ready.

08

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.
medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.

medium

Review upstream issue

The source signal needs review before production use.