khive

A research knowledge graph runtime for agents that need structure: typed substrates, closed taxonomies, and a verb-consolidated MCP surface.

Vector search finds similar text. A knowledge graph finds structure: lineages, dependencies, contradictions, gaps. khive gives an agent a typed, queryable graph that grows as it works.

crates.io · GitHub · License: Apache 2.0

For AI agents

• /llms.txt: short project summary + a linked index of every doc page
• /llms-full.txt: every doc page, concatenated, in one fetch
• /md/*.md: raw, unconverted markdown for each page (also linked from the bottom of every page)

Documentation

• Getting Started: install, connect, first session
• Knowledge Graph Modeling: entity kinds, edge relations, modeling patterns
• Memory and Recall: episodic vs semantic, salience, decay
• Search and Retrieval: FTS, vector, hybrid fusion, reranking
• GTD Task Management: task lifecycle, priorities, dependencies
• Prompt Cookbook: ready-to-use verb patterns
• API Reference: full verb catalog, params, DSL examples

Demos

Runnable transcripts, captured against a scratch database, in the repo’s demos/ directory:

• research-ingest: create entities, link them, search, and traverse the graph
• gtd-memory: task lifecycle and salience-weighted memory recall

Install

cargo install kkernel

kkernel is the single shipped binary; kkernel mcp serves the MCP request surface. Full install and MCP client setup: Getting Started.

Reference

• AGENTS.md: full verb reference for agents using khive
• Architecture Decision Records: the design contract

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Raw markdown for this page: /md/index.md