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Ramp MCP Server

by ramp-public

ramp-mcp: A Ramp MCP server

Overview

A Model Context Protocol server for retrieving and analyzing data or running tasks for Ramp using Developer API. In order to get around token and input size limitations, this server implements a simple ETL pipeline + ephemeral sqlite database in memory for analysis by an LLM. All requests are made to demo by default, but can be changed by setting RAMP_ENV=prd. Large datasets may not be processable due to API and/or your MCP client limitations.

Tools

Database tools

Tools that can be used to setup, process, query, and delete an ephemeral database in memory.

  1. process_data

  2. execute_query

  3. clear_table

Fetch tools

Tools that can be used to fetch data directly

  1. get_ramp_categories

  2. get_currencies

Load tools

Loads data to server which the client can fetch. Based on the tools you wish to use, ensure to enable those scopes on your Ramp client and include the scopes when starting the server as a CLI argument.

Tool

Scope

load_transactions

transactions:read

load_reimbursements

reimbursements:read

load_bills

bills:read

load_locations

locations:read

load_departments

departments:read

load_bank_accounts

bank_accounts:read

load_vendors

vendors:read

load_vendor_bank_accounts

vendors:read

load_entities

entities:read

load_spend_limits

limits:read

load_spend_programs

spend_programs:read

load_users

users:read

For large datasets, it is recommended to explicitly prompt Claude not to use REPL and to keep responses concise to avoid timeout or excessive token usage.

Related MCP server: Brex MCP Server

Setup

Ramp Setup

  1. Create a new client from the Ramp developer page (Profile on top right > Developer > Create app)

  2. Grant the scopes you wish (based on tools) to the client and enable client credentials (Click on App > Grant Types / Scopes)

  3. Include the client ID and secret in the config file as well as the scopes you wish to use

Local Setup

  1. Clone this Github repo via git clone git@github.com:ramp/ramp-mcp.git or equivalent

  2. Install uv

Usage

Run the MCP server from your CLI with:

RAMP_CLIENT_ID=... RAMP_CLIENT_SECRET=... RAMP_ENV=<demo|prd> uv run ramp-mcp -s <COMMA-SEPARATED-SCOPES>

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "ramp-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/<ABSOLUTE-PATH-TO>/ramp-mcp", // make sure to update this path
        "run",
        "ramp-mcp",
        "-s",
        "transactions:read,reimbursements:read"
      ],
      "env": {
        "RAMP_CLIENT_ID": "<CLIENT_ID>",
        "RAMP_CLIENT_SECRET": "<CLIENT_SECRET>",
        "RAMP_ENV": "<demo|qa|prd>"
      }
    }
  }
}

If this file doesn't exist yet, create one in /<ABSOLUTE-PATH-TO>/Library/Application Support/Claude/

License

Copyright (c) 2025, Ramp Business Corporation All rights reserved. This source code is licensed under the MIT License found in the LICENSE file in the root directory of this source tree.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

  • The Ramp MCP server enables users to securely connect Ramp with AI assistants like ChatGPT and Claude to query financial data and take actions using natural language. It transforms Ramp's developer API into a SQL interface that LLMs can query, allowing admins to analyze spend trends, identify cost savings, and run complex SQL analyses on comprehensive datasets (transactions, purchase orders, vendors, users), while all users can manage cards, view transactions, request reimbursements, and get expense policy answers.

  • The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.

  • A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…

  • Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server

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