Kilonova MCP

io.github.MilnaOS由 GitHub 帳號 MilnaOS 發布v0.1.1更新於 Oct 24, 2026

Persistent local knowledge for AI coding agents with structured records, search, and DOT context.

已驗證STDIO僅桌面知識與記憶開發者工具

概覽

AI 產生的概覽

供 AI 編程助理使用的本機檔案式知識庫:以結構化記錄保存專案狀態、決策與模式,並在後續工作階段重新載入。

可以做什麼
  • 載入 DOT(事實文件)參考文件到上下文中,並透過目錄只取所需章節
  • 依主題、實體類型與名稱搜尋、寫入與讀取結構化記錄,寫入時與既有記錄合併
  • 列出知識庫主題與記錄數量,並檢視某實體類型的欄位結構
  • 檢視知識庫大小與記錄統計,並可將知識庫鏡像備份到 OneDrive(支援試跑)
適用情境
適合在同一批專案上跨多次工作階段使用編程助理,希望決策、慣例與進行中的任務能保留下來、不必每次重新說明的狀況。也適合想以自訂結構在本機保存專案知識、不依賴雲端服務的團隊。
執行需求
以本機 Python 程序執行,從 PyPI 安裝(pip install kilonova-mcp),並以 python -m kilonova_mcp 啟動。需要一個知識庫目錄,由環境變數 KILONOVA_KB_ROOT 指定或使用平台預設路徑。起始 schema 與 CLAUDE.md 範本需手動複製。僅支援桌面端。
安裝前請注意
助理可以寫入與更新知識庫記錄,儲存內容會隨之變動,建議留意實際存了什麼。備份工具會把知識庫鏡像到 OneDrive,等於將本機專案筆記複製到第三方雲端服務。知識庫可能包含內部架構與決策,請將 KILONOVA_KB_ROOT 指向合適的位置。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Kilonova MCP,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

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 decisionSession 2: dot_load → Claude already knows. No recap needed.

Install

bash
pip install kilonova-mcp

Or from source:

bash
git clone https://github.com/MilnaOS/kilonova-mcpcd kilonova-mcppip install -e .

Wire Up Claude Code

Add to ~/.claude/settings.json:

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 two sections:

---TOC---1:Projects|1.1:My_Project2:Active_Tasks3:Decisions
---CARDS---
## [1] PROJECTS### [1.1] My ProjectSTATUS: activeNEXT: wire up the auth flow

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 typeUse for
project_stateCurrent status, location, next action per project
decisionArchitectural choices with rationale
patternCode conventions, gotchas, file locations
active_taskIn-flight work across sessions
session_noteEnd-of-session summaries

Tools

ToolDescription
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:

json
// 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

來源:README.md,提交 ccb7767

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.1最新Sep 16, 2026

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