Content
<div align="center">
<br>
<img src="docs/assets/banner.png" alt="Friday - Persistent Cognitive Memory for AI Coding Agents" width="100%" style="border-radius: 12px; border: 1px solid #1e293b;" />
<br><br>
<h1>
<img src="https://em-content.zobj.net/source/apple/391/high-voltage_26a1.png" height="32px" align="center"/>
Friday
</h1>
<p>
An open-source, self-hosted <strong>persistent cognitive memory layer</strong> for AI coding agents (Cursor, Claude, VS Code).<br>
Persists architecture decisions, schemas, and preferences across sessions via the Model Context Protocol (MCP).
</p>
<br>
<a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-ec4899?style=flat-square" alt="MIT License"/></a>
<a href="https://python.org"><img src="https://img.shields.io/badge/python-3.11+-3776AB?style=flat-square&logo=python&logoColor=white" alt="Python 3.11+"/></a>
<a href="https://fastapi.tiangolo.com"><img src="https://img.shields.io/badge/FastAPI-0.115-009688?style=flat-square&logo=fastapi&logoColor=white" alt="FastAPI"/></a>
<a href="https://neo4j.com"><img src="https://img.shields.io/badge/Neo4j-5.15-4581C3?style=flat-square&logo=neo4j&logoColor=white" alt="Neo4j"/></a>
<a href="docker-compose.yml"><img src="https://img.shields.io/badge/docker-compose-2496ED?style=flat-square&logo=docker&logoColor=white" alt="Docker"/></a>
<a href="mcp/server.py"><img src="https://img.shields.io/badge/MCP-protocol-7c3aed?style=flat-square" alt="MCP"/></a>
<a href="https://glama.ai/mcp/servers/itskie/friday"><img src="https://glama.ai/mcp/servers/itskie/friday/badges/score.svg" alt="Glama MCP Server"/></a>
<a href="CONTRIBUTING.md"><img src="https://img.shields.io/badge/PRs-welcome-ff69b4?style=flat-square" alt="PRs Welcome"/></a>
<a href="https://github.com/itskie/friday/stargazers"><img src="https://img.shields.io/github/stars/itskie/friday?style=flat-square&color=f59e0b" alt="Stars"/></a>
<br><br>
<table>
<tr>
<td align="center"><a href="#-60-second-quickstart"><b>🚀 Quickstart</b></a></td>
<td align="center"><a href="#-ide-setup--10-seconds"><b>🔌 IDE Setup</b></a></td>
<td align="center"><a href="#-features"><b>✨ Features</b></a></td>
<td align="center"><a href="#-api-reference"><b>📡 API Docs</b></a></td>
<td align="center"><a href="#-architecture"><b>🏗️ Architecture</b></a></td>
<td align="center"><a href="#-roadmap"><b>🗺️ Roadmap</b></a></td>
</tr>
</table>
<br><br>
<img src="docs/assets/neural_studio.png" alt="Friday Neural Studio — Live Knowledge Graph UI" width="100%" style="border-radius: 8px; border: 1px solid #1e293b;" />
<br>
<sub><i>Live Neural Studio — Obsidian-grade knowledge graph visualizer mapping real AI cognitive memory constellations.</i></sub>
<br><br>
</div>
---
## Problem: Session Amnesia & Token Overhead
Modern coding assistants (Cursor, Claude Code, Copilot, Antigravity) initialize each chat thread without cross-session memory. While developers frequently mitigate this using project documentation (`AGENTS.md`, prompt templates, or manual file references), this workflow presents two major bottlenecks:
1. **Context Window & Token Inefficiency**: Injecting massive architecture documents or having agents repeatedly read entire repository directories consumes thousands of context tokens on every single query.
2. **Loss of Incremental Decisions**: Ephemeral decisions—such as chosen dependency versions, schema adjustments, or bug fix rationale made in prior sessions—are lost when a session resets, forcing developers to repeatedly re-explain core constraints.
---
## Architecture & Solution
Friday runs as an open-source, self-hosted Model Context Protocol (MCP) server. Instead of dumping entire documentation files into prompt context, Friday exposes 4 targeted tools (`add_memory`, `add_fact`, `memory_search`, `get_context`) backed by a multi-tier storage engine:
- **Semantic Memory (Mem0)**: Preserves past decisions, preferences, and workflows across sessions.
- **Targeted Vector Search (ChromaDB)**: Retrieves only the exact memory snippets relevant to the immediate query.
- **Relational Knowledge Graph (Neo4j)**: Automatically extracts entities and relationships in the background, mapping connections between components, schemas, and dependencies.
- **Neural Studio**: Embedded web visualizer to inspect and query the knowledge graph in real time.
```
┌──────────────────────────────────────────────────────────────────────┐
│ YOUR AI AGENT (Cursor / Claude / Antigravity / VS Code) │
└──────────────────────────────┬───────────────────────────────────────┘
│
4 MCP Tools (stdio transport)
├── add_memory
├── add_fact
├── memory_search
└── get_context
│
▼
┌──────────────────────────────────────────────────────────────────────┐
│ FRIDAY BRAIN (FastAPI) │
│ │
│ Layer 2: Mem0 Layer 3: ChromaDB Layer 4: Neo4j │
│ ┌──────────────────┐ ┌─────────────────┐ ┌───────────────┐ │
│ │ Semantic Memory │ │ Vector Search │ │ Knowledge │ │
│ │ │ │ │ │ Graph │ │
│ │ • Cross-session │ │ • 90% fewer │ │ ────────── │ │
│ │ persistence │ │ tokens via │ │ ● WebApp │ │
│ │ • Contextual │ │ targeted │ │ ● Auth │ │
│ │ similarity │ │ retrieval │ │ ● Payments │ │
│ └──────────────────┘ └─────────────────┘ └───────────────┘ │
│ │
│ ⚡ Auto-Graph Engine │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ Every memory → LLM extraction → Neo4j nodes + edges │ │
│ │ Zero manual linking. Your knowledge base wires itself. │ │
│ └─────────────────────────────────────────────────────────────┘ │
│ │
│ 🎨 Neural Studio │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ Obsidian-grade live knowledge graph browser │ │
│ │ Spread slider • Filters • Inspector drawer • Full CRUD │ │
│ └─────────────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────────────┘
```
---
## Comparison: Static Prompts vs. Persistent Graph Memory
| Capability | Static Prompts / AGENTS.md | Friday (MCP + Neo4j + Vector) |
| :--- | :---: | :---: |
| **Cross-Session Memory** | ❌ Lost on thread reset | ✅ Persisted in database |
| **Context Retrieval** | ⚠️ Brute-force re-reading entire files | ✅ Targeted semantic & graph queries |
| **Entity Relationships** | ❌ Unstructured flat text | ✅ Neo4j Knowledge Graph |
| **Graph Generation** | ❌ Manual maintenance | ✅ Autonomous background extraction |
| **Visual Inspection** | ❌ None | ✅ Live browser UI (Neural Studio) |
| **Audit Trail** | ❌ None | ✅ Immutable versioned facts ledger |
| **Infrastructure** | Local files | 100% Self-hosted (Docker Compose) |
---
## Quickstart
> **Requirements:** [Docker](https://docker.com) + [Docker Compose](https://docs.docker.com/compose/) installed.
> That's literally it. No Python setup. No database config. No services to manage manually.
<br>
**Clone and configure**
```bash
git clone https://github.com/itskie/friday.git
cd friday
cp .env.example .env
```
**Fill in your `.env`** — takes 60 seconds
```env
# Set your own master password to protect your self-hosted server
FRIDAY_API_KEY=pick_any_secret_password_you_want
# DeepSeek (ultra-affordable — $0.14/M tokens)
# Get yours at: https://platform.deepseek.com
DEEPSEEK_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# Mem0 — generous free tier available
# Get yours at: https://mem0.ai
MEM0_API_KEY=m0-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# Neo4j password — you choose this
NEO4J_PASSWORD=change_to_something_strong
```
**Launch everything in one command**
```bash
docker compose up -d
```
This starts:
- 🧠 **Friday Brain** on `http://localhost`
- 🕸️ **Neo4j** on `http://localhost:7474`
- 🎨 **Neural Studio** at `http://localhost`
**Verify it's running**
```bash
curl http://localhost/health
# {"status":"healthy","layers":{"neo4j":"ok","mem0":"ok","facts":"ok (0 entries)"}}
```
**Store your first memory**
```bash
curl -X POST http://localhost/add \
-H "X-Brain-Key: your_key" \
-H "Content-Type: application/json" \
-d '{
"content": "We use JWT with 15min access tokens + 7-day refresh. Implementation in gateway/auth.py. Never store tokens in localStorage — httpOnly cookies only.",
"project": "MyApp"
}'
```
**Your AI now remembers. Forever.** ✅
---
## 🔌 Connecting Your Agents (MCP Setup)
Friday is designed to be the **central cognitive memory for all your AI coding tools**.
Whether Friday runs locally on your machine or on a **remote 24/7 cloud server (AWS EC2, VPS, Homelab)**, every agent connects to the **same unified memory** via the [Model Context Protocol (MCP)](https://modelcontextprotocol.io).
```
┌───────────────────────┐
│ Cursor (Desktop) │──┐
└───────────────────────┘ │
┌───────────────────────┐ │
│ Claude Code CLI │──┼── MCP Protocol (stdio transport)
└───────────────────────┘ │ FRIDAY_URL="http://your-server-ip:8000"
┌───────────────────────┐ │ BRAIN_API_KEY="your_secret_key"
│ Antigravity IDE │──┤
└───────────────────────┘ │
┌───────────────────────┐ │
│ Codex / Custom Agents │──┘
└───────────────────────┘
▼
┌──────────────────────────────┐
│ FRIDAY CENTRAL BRAIN │
│ (Self-Hosted on Cloud/EC2) │
│ FastAPI + Mem0 + Neo4j │
└──────────────────────────────┘
```
> 💡 **Shared Brain Superpower**: An architectural rule or decision stored by **Claude Code** in your terminal is immediately accessible to **Cursor**, **Antigravity IDE**, or **Codex** on your desktop. Zero manual syncing. One brain across your entire toolchain.
---
### Step-by-Step Client Configurations
Pick your client below, paste the configuration, and restart your agent:
<details>
<summary><b>⚡ Antigravity IDE</b></summary>
Add Friday to your Antigravity global MCP configuration at `~/.gemini/config/mcp_config.json`:
```json
{
"mcpServers": {
"friday": {
"command": "python",
"args": ["-m", "mcp.server"],
"cwd": "/path/to/friday",
"env": {
"FRIDAY_URL": "http://localhost:8000",
"BRAIN_API_KEY": "your_key_from_env"
}
}
}
}
```
*(If Friday runs on a remote server/EC2, change `FRIDAY_URL` to `http://<your-server-ip>:8000`)*
</details>
<details>
<summary><b>🤖 Claude Code (CLI)</b></summary>
Connect Claude Code to your Friday brain with one terminal command:
```bash
claude mcp add friday -e FRIDAY_URL="http://localhost:8000" -e BRAIN_API_KEY="your_key_from_env" -- python -m mcp.server
```
Or configure directly in `~/.claude.json` under `"mcpServers"`:
```json
{
"mcpServers": {
"friday": {
"command": "python",
"args": ["-m", "mcp.server"],
"cwd": "/path/to/friday",
"env": {
"FRIDAY_URL": "http://localhost:8000",
"BRAIN_API_KEY": "your_key_from_env"
}
}
}
}
```
</details>
<details>
<summary><b>🖱️ Cursor</b></summary>
Create or edit `.cursor/mcp.json` in your project root (or add globally in **Cursor Settings → MCP → Add New Server**):
```json
{
"mcpServers": {
"friday": {
"command": "python",
"args": ["-m", "mcp.server"],
"cwd": "/path/to/friday",
"env": {
"FRIDAY_URL": "http://localhost:8000",
"BRAIN_API_KEY": "your_key_from_env"
}
}
}
}
```
*(For a remote server, change `FRIDAY_URL` to `http://<your-server-ip>:8000`)*
</details>
<details>
<summary><b>📟 Codex & Autonomous Agents (CLI / Scripts)</b></summary>
Any custom agent, Codex script, or CI loop can interact with Friday in two ways:
**Option A: Via MCP stdio**
Run the MCP server directly as a subprocess using standard JSON-RPC 2.0.
**Option B: Direct HTTP REST API** (zero client dependencies)
```bash
# Store memory from any agent script
curl -X POST http://<your-server-ip>:8000/add -H "X-Brain-Key: your_key" -H "Content-Type: application/json" -d '{"content": "Refactored payment gateway to Stripe SDK v2.", "project": "MyApp"}'
# Retrieve relevant context before starting a prompt
curl -X POST http://<your-server-ip>:8000/search -H "X-Brain-Key: your_key" -H "Content-Type: application/json" -d '{"query": "How is payments structured?", "project": "MyApp"}'
```
</details>
<details>
<summary><b>💻 VS Code (Cline / Roo Code)</b></summary>
Add to your VS Code `settings.json` (or via Cline MCP settings):
```json
{
"cline.mcpServers": {
"friday": {
"command": "python",
"args": ["-m", "mcp.server"],
"cwd": "/path/to/friday",
"env": {
"FRIDAY_URL": "http://localhost:8000",
"BRAIN_API_KEY": "your_key_from_env"
}
}
}
}
```
</details>
<details>
<summary><b>🖥️ Claude Desktop</b></summary>
Edit your Claude Desktop configuration:
- **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`
```json
{
"mcpServers": {
"friday": {
"command": "python",
"args": ["-m", "mcp.server"],
"cwd": "/path/to/friday",
"env": {
"FRIDAY_URL": "http://localhost:8000",
"BRAIN_API_KEY": "your_key_from_env"
}
}
}
}
```
</details>
<br>
> 📁 Pre-built config templates for all clients are available in [`examples/`](examples/).
---
## Features
### Auto-Graph Engine — Automated Relationship Extraction
Every memory you store is automatically analyzed by an LLM (DeepSeek Flash).
Entities and relationships are extracted and wired into your Neo4j knowledge graph
**without any manual input from you.**
```
Input:
"MyApp uses Stripe for subscriptions. Plans: Free ($0), Pro ($19/mo), Team ($49/mo).
PayPal handles international. Webhooks at /api/payments/webhook."
Auto-extracted graph:
MyApp ────USES────────▶ Stripe
MyApp ────USES────────▶ PayPal
MyApp ────HAS_PLAN────▶ FreePlan [price: $0]
MyApp ────HAS_PLAN────▶ ProPlan [price: $19/mo]
MyApp ────HAS_PLAN────▶ TeamPlan [price: $49/mo]
Stripe ───WEBHOOK_AT──▶ /api/payments/webhook
```
No YAML. No manual tagging. Just store memories, and your knowledge graph builds itself.
---
### Neural Studio — Graph Visualization UI
<br>
<p align="center">
<img src="docs/assets/neural_studio.png" alt="Live Neural Studio Knowledge Graph" width="100%" style="border-radius: 10px; border: 1px solid #1e293b;" />
</p>
A browser-based visual explorer for your AI's knowledge — built with the same graph engine
that powers [Obsidian](https://obsidian.md)'s graph view.
**What you can do:**
- 🌌 Explore your entire knowledge base as a living constellation
- 🔍 Full-text search — camera auto-follows, inspector slides open
- 🎛️ **Spread slider** (1–10) — breathe space into dense graphs in real-time
- 🏷️ **Project filter chips** — isolate WebApp vs Auth vs Payments constellations
- 🖱️ **Click any node** → right-side inspector with facts, edges, actions
- ➕ Add / ✏️ Rename / 🗑️ Delete / 🔗 Connect — full CRUD via UI
- ❄️ **Freeze** physics to lock a layout, **Fit View** to reset camera
- ⚡ Live auto-refresh as new memories arrive
---
### Versioned Facts Ledger
Discrete facts (rules, preferences, constants) are stored with **immutable version history**.
Old versions are superseded, never deleted. You always have a full audit trail.
```python
# Store a fact
POST /facts → {"content": "We deploy on Ubuntu 22.04 LTS + systemd"}
# id: "a3f9e1b2", created_at: "2026-09-01", superseded: false
# 3 months later — upgraded
POST /facts → {"content": "We deploy on Ubuntu 24.04 LTS + Docker Compose"}
# Old fact: superseded: true ← preserved for history
# New fact: superseded: false ← active version
# Your AI always gets the active version. Past versions auditable via API.
GET /facts?include_superseded=true
```
---
### Semantic Search via Vector Embeddings
Instead of dumping your entire memory into every prompt, Friday uses ChromaDB vector search
to retrieve only the **most relevant context** for each query.
```python
# Traditional RAG — expensive and noisy
context = all_memories # 10,000 tokens of everything
# Friday — surgical precision
context = memory_search("JWT refresh token implementation")
# Returns: exactly the 3-5 memories about JWT, nothing else
# Cost: ~200 tokens vs 10,000 → 95% reduction
```
---
### Native MCP Toolset
Once connected, your AI agent automatically calls Friday's tools. No prompting required.
```
┌──────────────────────────────────────────────────────────────────┐
│ Tool │ When Your Agent Uses It │
├──────────────────┼───────────────────────────────────────────────┤
│ get_context │ At session START — loads all active facts │
│ │ + recent memories for instant orientation │
├──────────────────┼───────────────────────────────────────────────┤
│ memory_search │ Before answering architecture/design Q's │
│ │ "What's our auth pattern again?" │
├──────────────────┼───────────────────────────────────────────────┤
│ add_memory │ After implementing features, fixing bugs, │
│ │ making architectural decisions │
├──────────────────┼───────────────────────────────────────────────┤
│ add_fact │ For atomic rules that never change: │
│ │ stack choices, team preferences, standards │
└──────────────────┴───────────────────────────────────────────────┘
```
**Suggested system prompt addition:**
```
At the start of every session, call get_context to load my preferences and project context.
Before answering any technical question, call memory_search with the relevant topic.
After implementing features or making decisions, call add_memory to persist the context.
```
---
## Architecture
```
friday/
│
├── 📡 gateway/
│ └── main.py # FastAPI backbone — auth, routing, all endpoints
│
├── 🧩 layers/ # Pluggable memory backends (swap any layer)
│ ├── layer2_mem0.py # Semantic memory — Mem0 cloud API
│ ├── layer3_chroma.py # Vector store — ChromaDB (local)
│ └── layer4_neo4j.py # Knowledge graph — Neo4j
│
├── ⚡ pipelines/ # Background intelligence
│ ├── auto_graph.py # LLM entity extraction → Neo4j wiring
│ └── extract_facts.py # S3-style versioned fact management
│
├── 🔀 orchestrator/
│ └── router.py # Query routing — picks best layer per query type
│
├── 🔌 mcp/
│ └── server.py # MCP stdio server (JSON-RPC 2.0)
│ # ← This is what your IDE connects to
│
├── 🎨 studio/
│ └── index.html # Neural Studio — 1,400 lines, zero dependencies
│ # force-graph + d3 + vanilla JS
│
├── 🐳 docker-compose.yml # Neo4j + Friday Brain — production-ready
├── 🐳 Dockerfile # python:3.11-slim, multi-stage ready
├── 📦 requirements.txt # Pinned dependencies
└── 🌱 seed/ # Demo data to bootstrap a fresh install
├── facts.example.json
└── blueprints/demo_architecture.md
```
**Data Flow:**
```
[Your IDE]
→ MCP call: add_memory("We use Redis for rate limiting")
→ gateway/main.py → Mem0 store (sync)
→ auto_graph.py (background)
→ DeepSeek: extract entities
→ Neo4j: MERGE Redis node
→ Neo4j: CREATE edge (:App)-[:USES]->(:Redis)
← {"status": "added", "mem0_id": "abc123"}
```
---
## API Reference
All authenticated endpoints require the `X-Brain-Key` header.
🌐 = public endpoint (no auth required).
| Method | Endpoint | Auth | Description |
|:---:|:---|:---:|:---|
| `GET` | `/` 🌐 | — | Serves the Neural Studio UI |
| `GET` | `/health` 🌐 | — | Health check — reports status of all layers |
| `GET` | `/docs` 🌐 | — | Interactive Swagger UI |
| `POST` | `/add` | ✅ | Store a memory + trigger auto-graph wiring |
| `POST` | `/facts` | ✅ | Add or supersede a versioned fact |
| `GET` | `/facts` 🌐 | — | List all active facts |
| `GET` | `/facts?include_superseded=true` 🌐 | — | Full history including superseded |
| `POST` | `/search` | ✅ | Semantic search via Mem0 |
| `POST` | `/ingest` | ✅ | Ingest a document / architecture blueprint |
| `GET` | `/api/graph-data` 🌐 | — | All nodes + edges for Neural Studio |
| `GET` | `/api/search-quick?q=term` 🌐 | — | Fast fuzzy node name search |
| `POST` | `/api/node/create` | ✅ | Create entity node in graph |
| `DELETE` | `/api/node/{id}` | ✅ | Delete node + all relationships |
| `POST` | `/api/node/rename` | ✅ | Rename an entity node |
| `POST` | `/api/link/create` | ✅ | Create a typed relationship edge |
> Full interactive docs: `http://localhost/docs`
---
## Environment Variables
| Variable | Required | Default | Description |
|:---|:---:|:---|:---|
| `FRIDAY_API_KEY` | ✅ | — | Your self-hosted server secret (set by you to protect endpoints) |
| `DEEPSEEK_API_KEY` | ✅ | — | LLM key for auto-graph extraction |
| `MEM0_API_KEY` | ✅ | — | Mem0 key for semantic memory |
| `NEO4J_PASSWORD` | ✅ | — | Neo4j DB password (you set this) |
| `NEO4J_URI` | — | `bolt://neo4j:7687` | Neo4j connection string |
| `NEO4J_USER` | — | `neo4j` | Neo4j username |
| `DEEPSEEK_BASE_URL` | — | `https://api.deepseek.com` | LLM API base URL |
| `DEEPSEEK_MODEL` | — | `deepseek-chat` | LLM model name |
| `FACTS_PATH` | — | `/app/facts/facts.json` | Path for facts ledger file |
| `HOST` | — | `0.0.0.0` | Server bind address |
| `PORT` | — | `8000` | Server port |
**Where to get your keys (all have free tiers):**
| Service | Link | Cost |
|:---|:---|:---|
| **DeepSeek** | [platform.deepseek.com](https://platform.deepseek.com) | ~$0.14/M tokens — cheapest capable LLM |
| **Mem0** | [mem0.ai](https://mem0.ai) | Generous free tier |
| **Neo4j** | Bundled in Docker Compose | Free & local |
---
## Roadmap
**v1.0 — Foundation** ✅ *shipped*
- [x] FastAPI memory gateway with full REST API
- [x] Neo4j knowledge graph integration
- [x] Autonomous graph extraction engine (DeepSeek + Neo4j)
- [x] Neural Studio UI — Obsidian-grade graph browser
- [x] MCP server — Cursor / Antigravity / Claude Desktop / VS Code
- [x] S3-style versioned facts ledger
- [x] Docker Compose — 1-command self-hosted setup
- [x] ChromaDB semantic search layer
- [x] Full CRUD via Neural Studio (add / rename / delete / connect)
- [x] Per-project constellation namespacing
**v1.1 — Multi-User & DX** 🚧 *in progress*
- [ ] Multi-user support with isolated namespaces
- [ ] Python SDK (`pip install friday-client`)
- [ ] TypeScript/JavaScript SDK
- [ ] `friday` CLI — `friday add "..."`, `friday search "..."` from terminal
**v1.2 — Integrations** 📋 *planned*
- [ ] GitHub Actions bot — auto-store PR summaries as memories
- [ ] Slack integration — `/friday remember ...` from Slack
- [ ] Jira / Linear sync — auto-import tickets as project context
- [ ] VS Code extension — sidebar memory panel
**v2.0 — Cloud** 🌐 *future*
- [ ] Friday Cloud — managed, zero-infra option
- [ ] Team workspaces — shared memory across your engineering team
- [ ] Private beta waitlist
---
## Contributing
Friday is built in public and we'd love your contributions.
```bash
# Fork & clone
git clone https://github.com/YOUR_USERNAME/friday.git
cd friday
# Set up environment
cp .env.example .env
pip install -r requirements.txt
# Run tests — all must be green before PRing
python -m pytest tests/ -v
# ✅ 9 passed in 0.34s
# Create your branch
git checkout -b feat/your-amazing-feature
# Commit using conventional commits
git commit -m "feat: add X that does Y"
# Push & open PR
git push origin feat/your-amazing-feature
```
See [CONTRIBUTING.md](CONTRIBUTING.md) for full guidelines.
Browse [`good first issue`](https://github.com/itskie/friday/issues?q=label%3A%22good+first+issue%22) labels to find where to start.
---
## Security
Friday is designed for self-hosted deployment. A few notes:
- **API Key auth** — all write endpoints require `X-Brain-Key` header
- **Public read** — `/health`, `/facts` (read), `/api/graph-data`, and Neural Studio are public by default. If you expose Friday publicly, consider adding reverse-proxy authentication (e.g., Nginx basic auth or Cloudflare Access).
- **Secrets** — never commit your `.env`. It's in `.gitignore` by default.
- **Network** — by default, Friday binds to `0.0.0.0`. For local-only use, change to `127.0.0.1` in `.env`.
Found a vulnerability? Please open a **private** security advisory on GitHub rather than a public issue.
---
## License
MIT © 2026 Friday Contributors — see [LICENSE](LICENSE) for details.
---
<div align="center">
<br>
**Built for the AI-native developer generation.**
<br>
If Friday saved you from AI amnesia, please consider giving it a ⭐
It helps more developers discover the project and keeps us motivated.
<br>
[⭐ Star on GitHub](https://github.com/itskie/friday) ·
[🐛 Report Bug](https://github.com/itskie/friday/issues/new?template=bug_report.md) ·
[💡 Request Feature](https://github.com/itskie/friday/issues/new?template=feature_request.md) ·
[💬 Discussions](https://github.com/itskie/friday/discussions)
<br>
<sub>Made with ❤️ by developers who were tired of repeating themselves to their AI.</sub>
</div>
Connection Info
You Might Also Like
No recommendations available