Kilonova MCP
Persistent local knowledge for AI coding agents with structured records, search, and DOT context.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
kilonova-mcpclaude mcp add kilonova-mcp -e 'KILONOVA_KB_ROOT=<KILONOVA_KB_ROOT>' -- uvx kilonova-mcp==0.1.1
{
"mcpServers": {
"kilonova-mcp": {
"command": "uvx",
"args": [
"kilonova-mcp==0.1.1"
],
"env": {
"KILONOVA_KB_ROOT": "<KILONOVA_KB_ROOT>"
}
}
}
}
Environment variables
KILONOVA_KB_ROOTDirectory where Kilonova stores local knowledge bases. Defaults to a platform-appropriate local path.
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
Kilonova MCP
Persistent knowledge base tools for Claude Code.
Claude remembers your projects, decisions, and patterns across sessions — stored on your machine, no cloud required.
Built by AIM Studio · Free · MIT License
The Problem
Every Claude Code session starts cold. You re-explain your project structure, re-describe decisions you made last week, re-state what's in flight. Context burns fast.
The Solution: DOT + KB
Kilonova gives Claude a persistent knowledge base on your local machine. At session start, Claude loads your DOT (Document of Truth) — a compressed, structured reference doc with your project state, active tasks, decisions, and patterns. During the session, Claude writes new discoveries back to the KB. Next session, it's all there.
Session 1: Claude learns your architecture → kb_write saves the decision
Session 2: dot_load → Claude already knows. No recap needed.
Install
pip install kilonova-mcp
Or from source:
git clone https://github.com/MilnaOS/kilonova-mcp
cd kilonova-mcp
pip install -e .
Wire Up Claude Code
Add to ~/.claude/settings.json:
{
"mcpServers": {
"kilonova": {
"command": "python",
"args": ["-m", "kilonova_mcp"],
"env": {
"KILONOVA_KB_ROOT": "/path/to/your/kb"
}
}
}
}
Copy CLAUDE.md.template to ~/.claude/CLAUDE.md (or append to your existing one).
Quick Start
1. Create your first KB topic:
In Claude Code, just start writing:
mcp__kilonova__kb_write(
topic="claude_context",
entity_type="project_state",
name="my-project",
data={
"name": "my-project",
"status": "active",
"location": "/path/to/project",
"summary": "What this project is",
"next_action": "What to do next"
}
)
2. Load it next session:
mcp__kilonova__dot_load(topic="claude_context")
3. Search it:
mcp__kilonova__kb_search(topic="claude_context", query="authentication decision")
The DOT Format
A DOT is a plain text file with three sections:
---SYMBOLS---
[PR]=My Project (/path/to/project)
[DB]=Database (PostgreSQL on localhost:5432)
---TOC---
1:Projects|1.1:My_Project
2:Active_Tasks
3:Decisions
---CARDS---
## [1] PROJECTS
### [1.1] My Project
STATUS: active
NEXT: wire up the auth flow
Symbols compress repeated references. The TOC lets Claude fetch only the section it needs. Cards hold the actual content.
See example_dot/ for a starter template.
Starter Schema: claude_context
Copy schemas/claude_context/ into your KB directory under <kb_root>/claude_context/schemas/:
| Entity type | Use for |
|---|---|
project_state | Current status, location, next action per project |
decision | Architectural choices with rationale |
pattern | Code conventions, gotchas, file locations |
active_task | In-flight work across sessions |
session_note | End-of-session summaries |
Tools
| Tool | Description |
|---|---|
dot_load(topic) | Load full DOT document into context |
kb_search(topic, query) | Search records by natural language query |
kb_write(topic, entity_type, name, data) | Write/update a record (merges with existing) |
kb_load(topic, entity_type, name) | Load one specific record |
kb_topics() | List all KB topics and record counts |
kb_schema(topic, entity_type?) | Show field schema for an entity type |
corpus_status(topic) | Show KB size and record counts |
kb_backup(dry?) | Mirror KB to OneDrive |
Bring Your Own KB
Kilonova doesn't care what you store. Define your own schemas:
// kb/my_topic/schemas/component.json
{
"name": {"type": "string", "description": "Component name"},
"file": {"type": "string", "description": "Path to file"},
"purpose": {"type": "string", "description": "What it does"},
"dependencies": {"type": "array", "description": "What it depends on"}
}
Then write records to it and search them naturally.
Part of the Kilonova Ecosystem
Kilonova MCP is the free, standalone KB layer extracted from Milna OS — a full BYOK multi-model AI terminal. If you want the whole thing (parallel model legs, distillation engine, web ingestion, local+cloud hybrid inference), check out Milna OS.
MIT License · © AIM Studio
Frequently asked questions
What is Kilonova MCP?
Persistent local knowledge for AI coding agents with structured records, search, and DOT context.
How do I install Kilonova MCP?
It runs on your machine. In Claude Code: claude mcp add kilonova-mcp -e 'KILONOVA_KB_ROOT=<KILONOVA_KB_ROOT>' -- uvx kilonova-mcp==0.1.1. For other clients, paste the JSON configuration from this page into their MCP settings.
Does Kilonova MCP need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is Kilonova MCP open source?
Its code is public on GitHub, but the repository does not declare a standard license.
Who maintains Kilonova MCP?
It is published by MilnaOS. AI.tn lists it but does not maintain or endorse it.
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