create-snipara (NPX)

One-command setup for Snipara MCP + RLM-Runtime — context optimization, semantic memory, and safe code execution for AI agents.

npx create-snipara

What It Does

Installs snipara-mcp — MCP server for context-optimized documentation queries
Installs rlm-runtime — Safe code execution with Docker isolation
Configures .mcp.json — Ready for Claude Code, Cursor, Claude Desktop
Sets up hooks — Session memory automation (Claude Code)
Updates environment files — Adds API key configuration

Interactive Setup

Run npx create-snipara in your project directory. You'll be prompted for:

Prompt	Description
Project slug	Auto-detected from git remote or directory name
Project ID	Optional, for advanced use cases
API key type	Project key, Team key, Sign up, or Skip
API key	Your Snipara API key
AI client	Claude Code, Cursor, Claude Desktop, or other
Packages	Choose what to install (snipara-mcp, rlm-runtime)
LLM provider	OpenAI, Anthropic, or None (for `rlm run`/`rlm agent` CLI)
Run rlm init	Optional — configure execution environment (sandbox/docker/local)

Execution Environments

When you select RLM-Runtime during setup, you'll be asked if you want to run rlm init to configure the execution environment:

Environment	Description	Use Case
`sandbox`	RestrictedPython, safe stdlib only	Default, most secure
`docker`	Full Python in isolated container	Recommended for full features
`local`	Full access, no isolation	Development only

Security Recommendation

Use docker mode for production and untrusted code. local mode is only recommended for development and AI-generated code.

You can also configure the environment later by running rlm init manually.

API Key Requirements

Tool	Snipara API Key	LLM API Key (OpenAI/Anthropic)
`execute_python` MCP	Not needed	Not needed (your AI client is the LLM)
`rlm_context_query` MCP	Required	Not needed
`rlm_remember`/`rlm_recall`	Required	Not needed
`rlm run` / `rlm agent` CLI	Optional (for context)	Required

Key Types

Type	Description
Project API key	Access to a single project
Team API key	Access to all projects in your team

Command Line Options

Basic usage

npx create-snipara

With project API key

npx create-snipara --api-key rlm_your_project_key

With team API key (access all team projects)

npx create-snipara --team-key rlm_your_team_key

Specify project slug

npx create-snipara --slug my-project

Runtime only - no Snipara API key needed

npx create-snipara --runtime-only

Skip specific installations

npx create-snipara --skip-mcp # Skip snipara-mcp

npx create-snipara --skip-runtime # Skip rlm-runtime

npx create-snipara --skip-hooks # Skip Claude Code hooks

npx create-snipara --skip-test # Skip connection test

Accept all defaults (non-interactive)

npx create-snipara -y --api-key rlm_xxx --slug my-project

What Gets Created

.mcp.json

  "mcpServers": {

    "snipara": {

      "type": "http",

      "url": "https://api.snipara.com/mcp/your-project",

      "headers": {

        "X-API-Key": "rlm_your_key"

},

    "rlm-runtime": {

      "type": "http",

      "url": "http://localhost:8765/mcp",

      "headers": {}

Claude Code Hooks (if selected)

snipara-startup.sh — Restores session context
snipara-session.sh — Auto-remembers commits
snipara-compact.sh — Saves context before compaction

Environment Files

Updates .env.example and .env.local with:

Snipara Configuration

SNIPARA_API_KEY=your_api_key

SNIPARA_PROJECT_SLUG=your-project

RLM-Runtime LLM Provider (if configured)

OPENAI_API_KEY=sk-...

or

ANTHROPIC_API_KEY=sk-ant-...

After Installation

For Claude Code / Cursor

Restart your AI client
MCP tools are automatically available

For Claude Desktop

Restart Claude Desktop
Config is at ~/Library/Application Support/Claude/claude_desktop_config.json

RLM-Runtime Usage

MCP Tools (no LLM API key needed):

Your AI client (Claude, GPT, etc.) provides the LLM — no additional API key required.

Tool	Description
`execute_python`	Run Python in sandbox
`get_repl_context`	Get session variables
`set_repl_context`	Set session variables
`clear_repl_context`	Clear session

CLI Commands (requires LLM API key):

For rlm run and rlm agent, you need an LLM provider API key:

Set your LLM provider

export OPENAI_API_KEY=sk-...

or

export ANTHROPIC_API_KEY=sk-ant-...

Run commands

rlm init # Initialize configuration

rlm run --env docker # Run with Docker isolation

rlm agent "task" # Autonomous agent mode

rlm visualize # Launch trajectory dashboard

Available MCP Tools

After setup, you have access to 43+ MCP tools:

Category	Tools
Context	`rlm_context_query`, `rlm_ask`, `rlm_search`, `rlm_sections`
Planning	`rlm_plan`, `rlm_decompose`, `rlm_multi_query`
Memory	`rlm_remember`, `rlm_recall`, `rlm_memories`, `rlm_forget`
Execution	`execute_python`, `get_repl_context` (via RLM-Runtime)
Swarms	`rlm_swarm_create`, `rlm_claim`, `rlm_task_create`

Requirements

Node.js 18+
Python 3.10+ (for snipara-mcp and rlm-runtime)
Docker (optional, for RLM-Runtime isolation)

Next Steps

MCP Tools Reference

Learn about all available MCP tools and their parameters.

RLM-Runtime Integration

Deep dive into sandboxed Python execution.

Getting Started Guide

Complete setup guide for manual configuration.

Go to Dashboard

Start building with Snipara now.