Ramp
Interact with Ramp's Developer API to run analysis on your spend and gain insights leveraging LLMs
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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 that can be used to setup, process, query, and delete an ephemeral database in memory.
Installation
Installation instructions are not available yet.
Configuration
{
"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>"
}
}Capabilities
- Load financial data into an in-memory database
use `load_transactions`, `load_bills`, `load_reimbursements`, and other load tools to pull Ramp data into an ephemeral SQLite database for analysis.
- Query loaded data with SQL
run arbitrary SQL queries against the in-memory database using `execute_query` to filter, aggregate, or join loaded datasets.
- Fetch reference data directly
retrieve Ramp categories and supported currencies via `get_ramp_categories` and `get_currencies` without loading them into the database.
- Manage the ephemeral database
process raw API responses into queryable tables with `process_data` and clear tables using `clear_table` when done.
Tags
- finance
- data-analysis
- api
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