FastBCP MCP Server

A Model Context Protocol (MCP) server that exposes FastBCP functionality for exporting data from databases to files (CSV, TSV, JSON, BSON, Parquet, XLSX, Binary) with optional cloud storage targets.

Overview

FastBCP is a high-performance CLI tool for exporting data from databases to files. This MCP server wraps FastBCP 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_export_command

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

2. execute_export

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

3. validate_connection

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

4. list_supported_formats

List all supported source databases, output formats, and storage targets.

5. suggest_parallelism_method

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

6. get_version

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

Installation

Prerequisites

• Python 3.10 or higher
• FastBCP binary v0.29+ (obtain from Arpe.io)
• Claude Code or another MCP client

Setup

1. Clone or download this repository:

   cd /path/to/fastbcp-mcp
   

2. Install Python dependencies:

   pip install -r requirements.txt
   

3. Configure environment:

   cp .env.example .env
   # Edit .env with your FastBCP path
   

4. Add to Claude Code configuration (~/.claude.json):

   {
     "mcpServers": {
       "fastbcp": {
         "type": "stdio",
         "command": "python",
         "args": ["/absolute/path/to/fastbcp-mcp/src/server.py"],
         "env": {
           "FASTBCP_PATH": "/absolute/path/to/FastBCP"
         }
       }
     }
   }
   

5. Restart Claude Code to load the MCP server.

6. Verify installation:

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

Configuration

Environment Variables

Edit .env to configure:

# Path to FastBCP binary (required)
FASTBCP_PATH=./fastbcp/FastBCP

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

# Log directory (default: ./logs)
FASTBCP_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
application_intent	SQL Server application intent (ReadOnly/ReadWrite)

Output Options

Option	CLI Flag	Description
format	--format	Output format: csv, tsv, json, bson, parquet, xlsx, binary
file_output	--fileoutput	Output file path
directory	--directory	Output directory path
storage_target	--storagetarget	Storage: local, s3, s3compatible, azure_blob, azure_datalake, fabric_onelake
delimiter	--delimiter	Field delimiter (CSV/TSV)
quotes	--quotes	Quote character
encoding	--encoding	Output encoding
no_header	--noheader	Omit header row (CSV/TSV)
decimal_separator	--decimalseparator	Decimal separator (. or ,)
date_format	--dateformat	Date format string
bool_format	--boolformat	Boolean format: TrueFalse, OneZero, YesNo
parquet_compression	--parquetcompression	Parquet compression: None, Snappy, Gzip, Lz4, Lzo, Zstd
timestamped	--timestamped	Add timestamp to output filename
merge	--merge	Merge parallel output files

Export Options

Option	CLI Flag	Description
method	--method	Parallelism method
distribute_key_column	--distributeKeyColumn	Column for data distribution
degree	--degree	Parallelism degree (default: 1)
load_mode	--loadmode	Append or Truncate
batch_size	--batchsize	Batch size for export 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
settings_file	--settingsfile	Custom settings JSON file
log_level	--loglevel	Override log level (Information/Debug)
no_banner	--nobanner	Suppress banner output
license_path	--license	License file path or URL
cloud_profile	--cloudprofile	Cloud storage profile name

Usage Examples

PostgreSQL to CSV Export

User: "Export the 'orders' table from PostgreSQL (localhost:5432, database: sales_db,
       schema: public) to CSV file at /tmp/orders.csv. Use parallel export."

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

Export to Parquet with Compression

User: "Export the 'transactions' table from SQL Server to Parquet format
       with Snappy compression, saved to /data/exports/."

Claude Code will use parquet format with parquet_compression set to Snappy.

Export to S3

User: "Export the 'users' table from PostgreSQL to CSV on S3 bucket
       s3://my-bucket/exports/ using my AWS profile."

Claude Code will use storage_target=s3 with cloud_profile.

Check Version and Capabilities

User: "What version of FastBCP is installed?"

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

Two-Step Safety Process

This server implements a mandatory two-step process:

1. Preview - Always use preview_export_command first
2. Execute - Use execute_export 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, --sourceconnectstring, -x, -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

fastbcp-mcp/
  src/
    __init__.py
    server.py          # MCP server (tool definitions, handlers)
    fastbcp.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. FastBCP itself is a separate product from Arpe.io.

Related Links

• FastBCP Documentation
• Model Context Protocol