Rami Levy

v1.0.0Finance & Fintechstable

MCP server for rami levy

finance-fintech
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What is Rami Levy?

Rami Levy is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server for rami levy

MCP server for rami levy

This server falls under the Finance & Fintech category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • MCP server for rami levy

Use Cases

Retail finance integration
Payment processing
Community

Maintainer

LicenseMIT
Languagetypescript
Versionv1.0.0
UpdatedN/A
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

NPM

npx -y rami-levy

Manual Installation

npx -y rami-levy

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

Frequently Asked Questions about Rami Levy

What is Rami Levy?

Rami Levy is a Model Context Protocol (MCP) server that mcp server for rami levy It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Rami Levy?

Install via npm with the command: npx -y rami-levy. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).

Which AI clients work with Rami Levy?

Rami Levy works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Rami Levy free to use?

Yes, Rami Levy is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More Finance & Fintech MCP Servers

Explore all finance & fintech servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "rami-levy": { "command": "npx", "args": ["-y", "rami-levy"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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