Skip to main content

Persistent knowledge base MCP server for Claude Code — remember everything across sessions

Project description

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kilonova_mcp-0.1.0.tar.gz (10.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

kilonova_mcp-0.1.0-py3-none-any.whl (10.8 kB view details)

Uploaded Python 3

File details

Details for the file kilonova_mcp-0.1.0.tar.gz.

File metadata

  • Download URL: kilonova_mcp-0.1.0.tar.gz
  • Upload date:
  • Size: 10.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for kilonova_mcp-0.1.0.tar.gz
Algorithm Hash digest
SHA256 b76a4906a2a4f2fdad397812d9f50c873eae7bf3161dcae153e978b442983c3f
MD5 1a76339cf3b8c917c4a93a638fc8edf0
BLAKE2b-256 35c92e89796c0e8caa6629a92958d57e7382bcd9123ef6f4155015994a917de7

See more details on using hashes here.

File details

Details for the file kilonova_mcp-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: kilonova_mcp-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 10.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for kilonova_mcp-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 89ae08c3b8ed694bec03470af85e86eaa171af0e4df8225e7abe3f53094b57ea
MD5 81e1b8f779439b95fbd8691e0eb98a95
BLAKE2b-256 95684b4440c387f3c3157b1a69f914b45514685d4f716f908d2be53a76ec8cb3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page