Components, versions and architecture
YantrikDB ships as three pieces on independent release trains. This page is the full reference; the homepage carries only the current version strip.
Three components, three version lines
Section titled “Three components, three version lines”YantrikDB ships as three independently-released pieces, and they carry different version numbers on purpose — the engine you embed, the server you deploy, and the MCP bridge your agent talks to each move on their own release train.
| Component | Version | Install | What it is |
|---|---|---|---|
Core engine — yantrikdb | {v.engine} | pip install yantrikdbcargo add yantrikdb | The embeddable memory engine (Rust + Python bindings), one logical SQLite database: recall that fuses BM25 lexical scoring with the vector lane and optionally reranks, an explain surface for why a result came back, knowledge graph, conflict detection on recognised relations, temporal decay, consolidation, AES-256-GCM encryption at rest. This is what most people mean by “YantrikDB”. |
Server — yantrikdb-server | {v.server} | docker pull ghcr.io/yantrikos/yantrikdb | The network database that wraps the engine: multi-tenant HTTP API, YRP native replication with leader election, server-side clustered packs, encryption at rest. |
MCP — yantrikdb-mcp | {v.mcp} | pip install yantrikdb-mcp | The MCP server — plugs the engine into Claude Code, Codex, Cursor, Windsurf, Copilot, and any MCP-compatible agent. Runs embedded, or points at a server. |
If you saw one version quoted somewhere and a different one elsewhere, that’s these three lines being read as one number. They aren’t. The server is at {v.server}; the engine is at {v.engine}; the MCP bridge is at {v.mcp}.
Latest releases
Section titled “Latest releases”Everything below this line describes what the engine does, not which release it arrived in. For the chronology — every tag, every set of notes, oldest to newest — read the releases page on GitHub.
Architecture
Section titled “Architecture”| Index | What It Does | Example Query |
|---|---|---|
| Vector (HNSW) | Semantic similarity search | ”What did the user say about work?” |
| Graph | Entity relationships & reasoning | ”Who works at what company?” |
| Temporal | Time-aware retrieval | ”What happened last Tuesday?” |
| Decay Heap | Importance with biological time decay | Memories fade like human memory |
| Key-Value | Instant fact lookup | ”User’s timezone is CST” |
All five indexes query the same data. A single recall() call blends signals from all of them into one relevance-conditioned score.