MCP server for LakeXpress — automated database-to-cloud data pipeline as Parquet
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"lakexpress": {
"cwd": "/path/to/lakexpress-mcp",
"env": {
"LAKEXPRESS_PATH": "/path/to/LakeXpress",
"FASTBCP_DIR_PATH": "/path/to/FastBCP/",
"LAKEXPRESS_LOG_DIR": "./logs",
"LAKEXPRESS_TIMEOUT": "3600"
},
"args": [
"-m",
"src.server"
],
"command": "python"
}
}
}Are you the author?
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A Model Context Protocol (MCP) server for LakeXpress — a database to Parquet export tool with sync management and data lake publishing.
No automated test available for this server. Check the GitHub README for setup instructions.
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A Model Context Protocol (MCP) server for LakeXpress — a database to Parquet export tool with sync management and data lake publishing.
pip install -e ".[dev]"
Add to your Claude Code MCP settings:
{
"mcpServers": {
"lakexpress": {
"command": "python",
"args": ["-m", "src.server"],
"cwd": "/path/to/lakexpress-mcp",
"env": {
"LAKEXPRESS_PATH": "/path/to/LakeXpress",
"LAKEXPRESS_TIMEOUT": "3600",
"LAKEXPRESS_LOG_DIR": "./logs",
"FASTBCP_DIR_PATH": "/path/to/FastBCP/"
}
}
}
}
Or using the installed entry point:
{
"mcpServers": {
"lakexpress": {
"command": "lakexpress-mcp",
"env": {
"LAKEXPRESS_PATH": "/path/to/LakeXpress",
"FASTBCP_DIR_PATH": "/path/to/FastBCP/"
}
}
}
}
preview_commandBuild and preview any LakeXpress CLI command without executing it. Supports all 14 subcommands with full parameter validation.
execute_commandExecute a previously previewed command. Requires confirmation: true as a safety mechanism.
validate_auth_fileValidate that an authentication file exists, is valid JSON, and optionally check for specific auth_id entries.
list_capabilitiesList all supported source databases, log databases, storage backends, publishing targets, compression types, and available commands.
suggest_workflowGiven a use case (source DB type, storage destination, optional publish target), suggest the full sequence of LakeXpress commands with example parameters.
get_versionReport the detected LakeXpress binary version and capabilities.
# 1. Initialize the log database (first-time setup)
LakeXpress logdb init -a auth.json --log_db_auth_id export_db
# 2. Create a sync configuration
LakeXpress config create -a auth.json --log_db_auth_id export_db \
--source_db_auth_id prod_db --source_schema_name sales \
--output_dir ./exports --compression_type Zstd
# 3. Execute the sync
LakeXpress sync --sync_id <sync_id>
# 4. Check status
LakeXpress status -a auth.json --log_db_auth_id export_db --sync_id <sync_id>
| Variable | Default | Description |
|---|---|---|
LAKEXPRESS_PATH | ./LakeXpress | Path to the LakeXpress binary |
LAKEXPRESS_TIMEOUT | 3600 | Command execution timeout in seconds |
LAKEXPRESS_LOG_DIR | ./logs | Directory for execution logs |
FASTBCP_DIR_PATH | (empty) | Path to FastBCP binary directory (auto-fills fastbcp_dir_path parameter) |
LOG_LEVEL | INFO | Logging level (DEBUG, INFO, WARNING, ERROR) |
# Install dev dependencies
pip install -e ".[dev]"
# Run tests
python -m pytest tests/ -v
# Run with coverage
python -m pytest tests/ -v --cov=src --cov-report=term-missing