NOUZ MCP Server
MCP Server for local knowledge management. Semantic + keywords + tags
README
NOUZ — MCP Server for local knowledge management
v2.1.0
Install
pip install -r requirements.txt
Run
export OBSIDIAN_ROOT=./obsidian
export EMBED_PROVIDER=ollama # openai, gigachat
python server.py
Config
Edit config.yaml:
| Field | Type | Description |
|---|---|---|
mode |
string | luca / prizma / sloi |
levels |
dict | core=1, pattern=2, module=3, quant=4, artifact=5 |
thresholds.semantic_bridge_threshold |
float | 0.55 default |
etalons |
list | Core signs with text for embedding |
prizma_modes |
dict | Keywords per thinking style |
Tools
Basic
read_file(path)— read note with YAML frontmatterwrite_file(path, content, metadata)— write note with YAMLlist_files(level, sign, tags, subfolder)— filter filesindex_all(with_embeddings)— index to DBembed(text)— get embedding
Navigation
get_parents(path)— files linking to this fileget_children(path)— files this file links to
Semantics (prizma / sloi)
calibrate_cores()— recalculate etalon embeddingsrecalc_signs()— recalculate sign_autorecalc_core_mix()— recalculate core_mixsuggest_metadata(path)— suggest level/signsuggest_parents(path)— suggest links by embeddingsformat_entity_compact(path)— entity formula
Modes
| Mode | Level Strict | Semantics | Description |
|---|---|---|---|
| luca | ❌ | ❌ | Simple graph |
| prizma | ❌ | ✅ | Semantic bridges + core_mix |
| sloi | ✅ | ✅ | Strict 5-level hierarchy |
File Format
---
level: 2
sign: Ψ
tags: [systems]
---
# Content here
Env Vars
| Variable | Default | Description |
|---|---|---|
OBSIDIAN_ROOT |
./obsidian | Vault path |
EMBED_PROVIDER |
openai | openai / gigachat / ollama |
EMBED_API_URL |
http://127.0.0.1:1234/v1 | API endpoint |
EMBED_MODEL |
— | Model name |
EMBED_API_KEY |
— | API key |
Copyright (c) 2026 KVANTRA. MIT License.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.