open-neural-substrate
Enables Claude to access and manage a persistent, human-readable knowledge graph of neurons, with semantic search, memory consolidation, and local ownership.
README
Open Neural Substrate (ONS)
A persistent, human-readable knowledge layer that acts as a second brain for any software.
What Is This?
ONS stores your knowledge — customers, tasks, notes, concepts, decisions — as neurons: structured records with natural-language content, embedding vectors, and weighted connections to other neurons.
Any software can query and update your knowledge through a local API:
- Claude connects via MCP (Model Context Protocol)
- Codex / GPT connects via function calling
- Scripts, automations, apps connect via plain HTTP
The substrate runs as a persistent local service on port 52830, starting at login. A background consolidation process — inspired by how brains consolidate memory during sleep — continuously strengthens useful connections, surfaces implicit clusters, prunes stale links, and refreshes embeddings.
Your neurons are like open weights for your mind: fully human-readable, machine-queryable, and owned entirely by you.
Quick Start
# Clone and setup
git clone <repo-url> ons && cd ons
make setup
# Start the server
make run
# In another terminal — create your first neuron
curl -X POST http://localhost:52830/upsert \
-H "Content-Type: application/json" \
-d '{
"type": "knowledge",
"title": "ONS Design Principles",
"content": "Every piece of knowledge is one neuron. Connections are first-class. All edits are local.",
"metadata": {"tags": ["architecture", "core"]}
}'
# Query it back
curl -X POST http://localhost:52830/query \
-H "Content-Type: application/json" \
-d '{"text": "design principles of the system"}'
Import Existing Knowledge
# Import a folder of markdown notes
make import-md DIR=~/notes
# Import JSON data (customers, tasks, etc.)
make import-json FILE=~/customers.json
# Export everything for backup
make export DIR=./backup
Connect Claude (MCP)
Add to your Claude Desktop or Claude Code config:
{
"mcpServers": {
"ons": {
"url": "http://localhost:52830/mcp",
"name": "open-neural-substrate"
}
}
}
Claude will now have access to your entire knowledge substrate as native tools.
Run as a Persistent Service
# Linux (systemd user service)
make install-service
# macOS (LaunchAgent)
make install-service
# Verify it's running
curl http://localhost:52830/health
The server starts at login and stays alive. Consolidation runs automatically during idle periods.
How It Works
Neurons (knowledge atoms) Edges (connections) Embeddings (search vectors)
┌──────────────────────┐ ┌─────────────────────┐ ┌──────────────────────────┐
│ id: neu_4f8a2c │ │ source → target │ │ neuron + model → vector │
│ type: customer │────▶│ type: has_task │ │ cached per-model │
│ title: Acme Corp │ │ strength: 0.92 │ │ refreshed on change │
│ content: (markdown) │ │ created_by: human │ │ 384-dim default │
│ version: 7 │ └─────────────────────┘ └──────────────────────────┘
└──────────────────────┘
│
▼ (during idle / sleep)
┌──────────────────────────────────────────────────────┐
│ Consolidation Cycle │
│ 1. Replay & strengthen used paths │
│ 2. Cluster frequently co-retrieved neurons │
│ 3. Decay unused connections │
│ 4. Re-embed stale neurons │
└──────────────────────────────────────────────────────┘
API Reference
| Endpoint | Method | Description |
|---|---|---|
/query |
POST | Semantic search + relational filtering. Returns ranked neurons. |
/upsert |
POST | Create or update a neuron. Auto-embeds. |
/rewire |
POST | Add, remove, or adjust connections. |
/delete/{id} |
DELETE | Soft-delete with version snapshot. |
/health |
GET | Service status + neuron count. |
/consolidation/status |
GET | Last run info + pending proposals. |
/consolidation/trigger |
POST | Manually trigger a consolidation cycle. |
Configuration
Copy .env.example to .env and adjust:
ONS_PORT=52830 # Server port
ONS_DB_PATH=~/.ons/brain.db # Database location
ONS_EMBEDDER=local # local | openai | anthropic
ONS_EMBED_MODEL=all-MiniLM-L6-v2
ONS_IDLE_MINUTES=30 # Idle time before consolidation
ONS_LOG_LEVEL=info
License
MIT
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.