MCP Data Pipeline Connector MCP Server

Universal data connector for CSV, Postgres, and REST APIs via DuckDB

Local serverstdio

What is the MCP Data Pipeline Connector MCP server?

MCP Data Pipeline Connector MCP server exists for a simple reason — assistants are far more useful when they can act on MCP Data Pipeline Connector directly instead of describing what you should do. Universal data connector for CSV, Postgres, and REST APIs via DuckDB.

What you get

One MCP server for all your data sources — with cross-source SQL joins and no external query service. DuckDB runs embedded in-process, so you can join a CSV file against a Postgres table against a REST API response in a single query, entirely on your machine. Agents work with your data without needing source-specific knowledge or multiple MCP server configs.

  • Unified query interface — SQL across all connected sources via DuckDB — including cross-source joins
  • Multiple source types — CSV/JSON files, PostgreSQL databases, and REST API endpoints in a single server
  • Auto schema detection — Infers column names and types from CSV headers and Postgres metadata
  • REST caching — REST API responses are cached with a configurable TTL to avoid redundant calls
  • Schema normalization — Maps source-specific types to a standard set (string, number, date, boolean, json)
  • In-process query engine — DuckDB runs embedded — no separate query service to install or manage

What the assistant can call

Once MCP Data Pipeline Connector is connected, these are the calls the assistant has available:

  • connect_source — list_sources
  • list_tables — get_schema
  • query — transform

Configuration and credentials

You will need one environment variable: POSTGRES_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

  • Node.js v20.19 or newer. - npm. - Optional: A running PostgreSQL instance for the Postgres connector.

Setting it up

Installation goes through your MCP client rather than a global install: point it at @modelcontextprotocol/inspector on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

Choosing this one

Among the database access options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. MCP Data Pipeline Connector's toolset — connect_source, list_tables, query — is a fair guide to whether it matches your workflow. It is maintained by dbsectrainer; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp data pipeline connector mcp server does with a few real requests.

Available tools

ToolWhat it does
connect_sourcelist_sources
list_tablesget_schema
querytransform

How to install the MCP Data Pipeline Connector MCP server

{
  "mcpServers": {
    "data-connector": {
      "command": "npx",
      "args": ["-y", "mcp-data-pipeline-connector@latest"]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Node.js v20.19 or newer. - npm. - Optional: A running PostgreSQL instance for the Postgres connector.
VariableDescriptionRequired
POSTGRES_URLEndpoint or connection string the server talks to.Yes

Example prompts to try

  • Use MCP Data Pipeline Connector to connect source.
  • Use MCP Data Pipeline Connector to list tables.
  • Use MCP Data Pipeline Connector to query.

Frequently asked questions

It connects MCP Data Pipeline Connector to MCP-compatible AI assistants such as Claude and Cursor, exposing 3 tools (connect_source, list_tables, query) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP Data Pipeline Connector directly.