VEKTOR Memory as Your Developer Second Brain: Complete Setup Guide

What You’re Building

By the end of this tutorial, VEKTOR Slipstream will be connected to your Claude Desktop instance as an MCP server. Claude will have access to persistent memory that survives between sessions, an encrypted credential vault for your secrets, a skill routing system that loads context on demand, and a stealth web fetch layer for gathering information without getting blocked.

This is not a chatbot with a longer context window. It is a second brain — a structured external memory that Claude can read from and write to, that accumulates knowledge over time, and that you control completely. Your data stays local. Your credentials never leave your machine. Nothing is stored in a cloud you don’t own.

Prerequisites

You need Node.js 18+ and Claude Desktop installed. That’s it. VEKTOR Slipstream ships as a self-contained package with its own SQLite database and doesn’t require any additional infrastructure.

Step 1: Install VEKTOR Slipstream

npm install -g vektor-slipstream

After installation, run the setup wizard:

vektor activate YOUR-LICENCE-KEY

The wizard will ask for your preferred AI provider (Anthropic, OpenAI, or local), your API key, and whether to configure the MCP server automatically. Answer yes to MCP setup — the wizard will write the correct config to your Claude Desktop config file.

Step 2: Verify the MCP Connection

Restart Claude Desktop. Open a new conversation and ask: "What VEKTOR tools do you have access to?" Claude should list the full suite of Slipstream tools: vektor_store, vektor_recall, vektor_recall_rrf, cloak_fetch, cloak_passport, cloak_ssh_exec, and the rest.

If Claude doesn’t see the tools, check your Claude Desktop config file. On macOS it’s at ~/Library/Application Support/Claude/claude_desktop_config.json. On Windows it’s at %APPDATA%\Claude\claude_desktop_config.json. The vektor entry should look like this:

"vektor": {
  "command": "node",
  "args": ["/path/to/vektor-slipstream/vektor.mjs", "mcp"]
}

Step 3: Store Your First Memory

Tell Claude something you want it to remember:

Store this in VEKTOR memory:
I'm building a Node.js API for a SaaS product.
The database is PostgreSQL on Railway.
The frontend is Next.js deployed on Vercel.
Importance: 4. Tags: project, stack, infrastructure.

Claude will call vektor_store and confirm. Next session, when you ask about your project, Claude will call vektor_recall before responding and will already know your stack.

Step 4: Set Up Your Skill Files

Skills are the most powerful part of the Slipstream architecture. A skill is a markdown file that tells Claude how to handle a specific category of task. When a task matches a skill description, Claude loads that skill’s context automatically rather than relying on your system prompt or a re-explanation every session.

Create a skills directory:

mkdir -p ~/vektor-skills/user

Create your first skill file at ~/vektor-skills/user/my-project.md:

---
name: my-project
description: Use when working on my SaaS project, API tasks, database queries, or deployment issues.
---

# My Project Context

Stack: Node.js API + PostgreSQL (Railway) + Next.js (Vercel)
Repo: github.com/yourusername/yourproject
Primary language: TypeScript

## Key Conventions
- All API routes use REST, not GraphQL
- Database migrations use db-migrate
- Environment variables are in Railway's dashboard, not .env files in repo

Store the skills path in memory so Claude always knows where to look:

Store in VEKTOR: Skills directory is at ~/vektor-skills. 
Always check cloak_cortex for available skills before starting work tasks.
Importance: 5. Tags: config, skills.

Step 5: Configure the Credential Vault

The cloak_passport vault uses AES-256 encryption to store credentials locally. The model never sees credential values — it only sees key names and tool results.

Store my Railway API token in the credential vault with key name "railway-token"

Claude will prompt you to paste the token value into a secure input. It stores the encrypted value and confirms. Now when you need Railway access, you just reference it by key name and Claude handles the authentication without the token ever appearing in conversation.

Common credentials to vault on day one: your main VPS SSH key, API tokens for services you access regularly, database connection strings for staging environments.

Step 6: Test the Memory Loop

The real test of a second brain is whether it reduces the re-explanation tax. Start a new Claude Desktop conversation — a completely fresh session with no history — and say:

What do you remember about my project setup?

Claude should call vektor_recall, retrieve the memories you stored, and respond with accurate context about your stack, conventions, and preferences. You didn’t re-explain anything. The second brain worked.

Step 7: Enable Web Traversal

Slipstream’s cloak_fetch and cloak_fetch_smart tools provide stealth web access using persistent browser identities with fingerprint rotation. This is useful for documentation lookups, changelog monitoring, and competitive research.

Tell Claude to use it instead of built-in web search when you need full page content:

Store in VEKTOR: When I ask you to fetch a URL or read a web page, 
use cloak_fetch_smart first (checks llms.txt for agent-friendly content), 
then fall back to cloak_fetch for rendered JavaScript pages.
Importance: 3. Tags: config, web.

What This Changes

The before-and-after is significant. Before: every new Claude session starts from zero. You re-explain your project. You re-explain your preferences. You re-paste credentials. You re-load context that should be permanent. After: Claude opens with your context already loaded. It knows your stack, your conventions, your credentials, your preferred tools. The session starts at the right altitude.

The second brain also compounds over time. Every decision you make, every convention you establish, every preference you articulate gets stored and becomes part of Claude’s baseline understanding of your work. Three months in, you have an agent that knows your codebase better than any new hire on day one.

Ongoing Maintenance

The system is designed to be low-maintenance, but a few habits help:

• At the end of significant work sessions, ask Claude to store a session summary: what was decided, what’s pending, what changed.
• Run vektor_recall_rrf occasionally to check what’s in memory and prune anything stale.
• Update skill files when your project conventions change — version-control them alongside your code.
• Use importance weights seriously: routine facts get 1-2, project-critical context gets 4-5. High-importance memories are weighted preferentially in recall.