Fasttransfer
FreeNot checkedMCP server for FastTransfer — high-performance parallel data transfer between databases
About
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
Clone or download this repository:
cd /path/to/fasttransfer-mcpInstall Python dependencies:
pip install -r requirements.txtConfigure environment:
cp .env.example .env # Edit .env with your FastTransfer pathAdd 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" } } } }Restart Claude Code to load the MCP server.
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:
- Preview - Always use
preview_transfer_commandfirst - Execute - Use
execute_transferwithconfirmation: 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
Install Fasttransfer in Claude Desktop, Claude Code & Cursor
unyly install fasttransfer-mcpInstalls 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-mcpFAQ
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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