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Fasttransfer

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MCP server for FastTransfer — high-performance parallel data transfer between databases

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MCP server for FastTransfer — high-performance parallel data transfer between databases

README

PyPI License: MIT MCP Registry

A Model Context Protocol (MCP) server that exposes FastTransfer functionality for efficient data transfer between various database systems.

Overview

FastTransfer is a high-performance CLI tool for transferring data between databases. This MCP server wraps FastTransfer functionality and provides:

  • Safety-first approach: Preview commands before execution with user confirmation required
  • Password masking: Credentials and connection strings are never displayed in logs or output
  • Intelligent validation: Parameter validation with database-specific compatibility checks
  • Smart suggestions: Automatic parallelism method recommendations
  • Version detection: Automatic binary version detection with capability registry
  • Comprehensive logging: Full execution logs with timestamps and results

MCP Tools

1. preview_transfer_command

Build and preview a FastTransfer command WITHOUT executing it. Shows the exact command with passwords masked. Always use this first.

2. execute_transfer

Execute a previously previewed command. Requires confirmation: true as a safety mechanism.

3. validate_connection

Validate database connection parameters (parameter check only, does not test actual connectivity).

4. list_supported_combinations

List all supported source-to-target database combinations.

5. suggest_parallelism_method

Recommend the optimal parallelism method based on source database type and table characteristics.

6. get_version

Report the detected FastTransfer binary version, supported types, and feature flags.

Installation

Prerequisites

  • Python 3.10 or higher
  • FastTransfer binary v0.16+ (obtain from Arpe.io)
  • Claude Code or another MCP client

Setup

  1. Clone or download this repository:

    cd /path/to/fasttransfer-mcp
    
  2. Install Python dependencies:

    pip install -r requirements.txt
    
  3. Configure environment:

    cp .env.example .env
    # Edit .env with your FastTransfer path
    
  4. Add to Claude Code configuration (~/.claude.json):

    {
      "mcpServers": {
        "fasttransfer": {
          "type": "stdio",
          "command": "python",
          "args": ["/absolute/path/to/fasttransfer-mcp/src/server.py"],
          "env": {
            "FASTTRANSFER_PATH": "/absolute/path/to/fasttransfer/FastTransfer"
          }
        }
      }
    }
    
  5. Restart Claude Code to load the MCP server.

  6. Verify installation:

    # In Claude Code, run:
    /mcp
    # You should see "fasttransfer: connected"
    

Configuration

Environment Variables

Edit .env to configure:

# Path to FastTransfer binary (required)
FASTTRANSFER_PATH=./fasttransfer/FastTransfer

# Execution timeout in seconds (default: 1800 = 30 minutes)
FASTTRANSFER_TIMEOUT=1800

# Log directory (default: ./logs)
FASTTRANSFER_LOG_DIR=./logs

# Log level (default: INFO)
LOG_LEVEL=INFO

Connection Options

The server supports multiple ways to authenticate and connect:

Parameter Description
server Host:port or host\instance (optional with connect_string or dsn)
user / password Standard credentials
trusted_auth Windows trusted authentication
connect_string Full connection string (excludes server/user/password/dsn)
dsn ODBC DSN name (excludes server/provider)
provider OleDB provider name
file_input File path for data input (source only, excludes query)

Transfer Options

Option CLI Flag Description
method --method Parallelism method
distribute_key_column --distributeKeyColumn Column for data distribution
degree --degree Parallelism degree (0=auto, >0=fixed, <0=CPU adaptive)
load_mode --loadmode Append or Truncate
batch_size --batchsize Batch size for bulk operations
map_method --mapmethod Column mapping: Position or Name
run_id --runid Run ID for logging
data_driven_query --datadrivenquery Custom SQL for DataDriven method
use_work_tables --useworktables Intermediate work tables for CCI
settings_file --settingsfile Custom settings JSON file
log_level --loglevel Override log level (error/warning/information/debug/fatal)
no_banner --nobanner Suppress banner output
license_path --license License file path or URL

Usage Examples

PostgreSQL to SQL Server Transfer

User: "Copy the 'orders' table from PostgreSQL (localhost:5432, database: sales_db,
       schema: public) to SQL Server (localhost:1433, database: warehouse, schema: dbo).
       Use parallel transfer and truncate the target first."

Claude Code will:
1. Call suggest_parallelism_method to recommend Ctid for PostgreSQL
2. Call preview_transfer_command with your parameters
3. Show the command with masked passwords
4. Explain what will happen
5. Ask for confirmation
6. Execute with execute_transfer when you approve

File Import via DuckDB Stream

User: "Import /data/export.parquet into the SQL Server 'staging' table
       using DuckDB stream."

Claude Code will use duckdbstream source type with file_input parameter.

Check Version and Capabilities

User: "What version of FastTransfer is installed?"

Claude Code will call get_version and display the detected version,
supported source/target types, and available features.

Two-Step Safety Process

This server implements a mandatory two-step process:

  1. Preview - Always use preview_transfer_command first
  2. Execute - Use execute_transfer with confirmation: true

You cannot execute without previewing first and confirming.

Security

  • Passwords and connection strings are masked in all output and logs
  • Sensitive flags masked: --sourcepassword, --targetpassword, --sourceconnectstring, --targetconnectstring, -x, -X, -g, -G
  • Use environment variables for sensitive configuration
  • Review commands carefully before executing
  • Use minimum required database permissions

Testing

Run the test suite:

# Run all tests
python -m pytest tests/ -v

# Run with coverage
python -m pytest tests/ --cov=src --cov-report=html

Project Structure

fasttransfer-mcp/
  src/
    __init__.py
    server.py          # MCP server (tool definitions, handlers)
    fasttransfer.py    # Command builder, executor, suggestions
    validators.py      # Pydantic models, enums, validation
    version.py         # Version detection and capabilities registry
  tests/
    __init__.py
    test_command_builder.py
    test_validators.py
    test_version.py
  .env.example
  requirements.txt
  CHANGELOG.md
  README.md

License

This MCP server wrapper is provided as-is. FastTransfer itself is a separate product from Arpe.io.

Related Links

from github.com/arpe-io/fasttransfer-mcp

Install Fasttransfer in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install fasttransfer-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add fasttransfer-mcp -- uvx fasttransfer-mcp

FAQ

Is Fasttransfer MCP free?

Yes, Fasttransfer MCP is free — one-click install via Unyly at no cost.

Does Fasttransfer need an API key?

No, Fasttransfer runs without API keys or environment variables.

Is Fasttransfer hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Fasttransfer in Claude Desktop, Claude Code or Cursor?

Open Fasttransfer on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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