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ramp-mcp: A Ramp MCP server

@ramp-public

Repository

Basic information

Category

Other

License

MIT

Transports

stdio

Author

ramp-public

About ramp-mcp: A Ramp MCP server

ramp_mcp

ramp-mcp: A Ramp MCP server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

ramp-mcp: A Ramp MCP server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is ramp-mcp?

A Model Context Protocol server for retrieving and analyzing data or running tasks for Ramp using the Ramp Developer API. It implements a simple ETL pipeline with an ephemeral SQLite database in memory to overcome token and input size limitations for LLM analysis. All requests default to the demo environment but can be changed to production by setting RAMP_ENV=prd.

How to use ramp-mcp?

Clone the repository, install uv, then run the server from the CLI with environment variables RAMP_CLIENT_ID, RAMP_CLIENT_SECRET, and optionally RAMP_ENV, plus the -s flag for comma-separated API scopes. For example:
RAMP_CLIENT_ID=... RAMP_CLIENT_SECRET=... RAMP_ENV=<demo|prd> uv run ramp-mcp -s transactions:read,reimbursements:read
Then load data using available load_* tools before querying the ephemeral database with process_data, execute_query, or clear_table.

Key features of ramp-mcp

  • ETL pipeline + ephemeral SQLite database for efficient LLM analysis.
  • Database tools: process_data, execute_query, clear_table.
  • Direct fetch tools: get_ramp_categories, get_currencies.
  • Load tools for transactions, reimbursements, bills, locations, departments, etc.
  • All data requests are scoped to the API permissions you grant.

Use cases of ramp-mcp

  • Analyze Ramp transaction data without hitting API token limits.
  • Run natural language queries against an ephemeral database of loaded Ramp entities.
  • Automate reconciliation or spending analysis for departments and categories.
  • Load and query vendor, bank account, or spend program data for reporting.

Frequently asked questions

1

How do I switch from the demo environment to production?

Set the environment variable `RAMP_ENV=prd` when starting the server.

2

What API scopes do I need to include?

Include scopes matching the load tools you plan to use (e.g., `transactions:read`, `reimbursements:read`). Grant these scopes to your Ramp client on the Developer page.

3

Why does the server use an ephemeral SQLite database?

To bypass token and input size limitations, the server loads data into an in‑memory SQLite database that an LLM can query efficiently. The database is deleted after the session.

4

What are known limitations around large datasets?

Large datasets may not be processable due to API rate limits or your MCP client’s token/input limits. It is recommended to explicitly prompt the LLM not to use REPL and to keep responses concise.

5

How do I set up the server with Claude Desktop?

Add a `ramp-mcp` entry to `claude_desktop_config.json` with the `uv` command, absolute directory path, and environment variables for `RAMP_CLIENT_ID`, `RAMP_CLIENT_SECRET`, and `RAMP_ENV`.

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