Files
lmiranda 89f0354ccc feat: add data-platform plugin (v4.0.0)
Add new data-platform plugin for data engineering workflows with:

MCP Server (32 tools):
- pandas operations (14 tools): read_csv, read_parquet, read_json,
  to_csv, to_parquet, describe, head, tail, filter, select, groupby,
  join, list_data, drop_data
- PostgreSQL/PostGIS (10 tools): pg_connect, pg_query, pg_execute,
  pg_tables, pg_columns, pg_schemas, st_tables, st_geometry_type,
  st_srid, st_extent
- dbt integration (8 tools): dbt_parse, dbt_run, dbt_test, dbt_build,
  dbt_compile, dbt_ls, dbt_docs_generate, dbt_lineage

Plugin Features:
- Arrow IPC data_ref system for DataFrame persistence across tool calls
- Pre-execution validation for dbt with `dbt parse`
- SessionStart hook for PostgreSQL connectivity check (non-blocking)
- Hybrid configuration (system ~/.config/claude/postgres.env + project .env)
- Memory management with 100k row limit and chunking support

Commands: /initial-setup, /ingest, /profile, /schema, /explain, /lineage, /run
Agents: data-ingestion, data-analysis

Test suite: 71 tests covering config, data store, pandas, postgres, dbt tools

Addresses data workflow issues from personal-portfolio project:
- Lost data after multiple interactions (solved by Arrow IPC data_ref)
- dbt 1.9+ syntax deprecation (solved by pre-execution validation)
- Ungraceful PostgreSQL error handling (solved by SessionStart hook)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-25 14:24:03 -05:00

388 lines
11 KiB
Python

"""
dbt MCP Tools.
Provides dbt CLI wrapper with pre-execution validation.
"""
import subprocess
import json
import logging
import os
from pathlib import Path
from typing import Dict, List, Optional, Any
from .config import load_config
logger = logging.getLogger(__name__)
class DbtTools:
"""dbt CLI wrapper tools with pre-validation"""
def __init__(self):
self.config = load_config()
self.project_dir = self.config.get('dbt_project_dir')
self.profiles_dir = self.config.get('dbt_profiles_dir')
def _get_dbt_command(self, cmd: List[str]) -> List[str]:
"""Build dbt command with project and profiles directories"""
base = ['dbt']
if self.project_dir:
base.extend(['--project-dir', self.project_dir])
if self.profiles_dir:
base.extend(['--profiles-dir', self.profiles_dir])
base.extend(cmd)
return base
def _run_dbt(
self,
cmd: List[str],
timeout: int = 300,
capture_json: bool = False
) -> Dict:
"""
Run dbt command and return result.
Args:
cmd: dbt subcommand and arguments
timeout: Command timeout in seconds
capture_json: If True, parse JSON output
Returns:
Dict with command result
"""
if not self.project_dir:
return {
'error': 'dbt project not found',
'suggestion': 'Set DBT_PROJECT_DIR in project .env or ensure dbt_project.yml exists'
}
full_cmd = self._get_dbt_command(cmd)
logger.info(f"Running: {' '.join(full_cmd)}")
try:
env = os.environ.copy()
# Disable dbt analytics/tracking
env['DBT_SEND_ANONYMOUS_USAGE_STATS'] = 'false'
result = subprocess.run(
full_cmd,
capture_output=True,
text=True,
timeout=timeout,
cwd=self.project_dir,
env=env
)
output = {
'success': result.returncode == 0,
'command': ' '.join(cmd),
'stdout': result.stdout,
'stderr': result.stderr if result.returncode != 0 else None
}
if capture_json and result.returncode == 0:
try:
output['data'] = json.loads(result.stdout)
except json.JSONDecodeError:
pass
return output
except subprocess.TimeoutExpired:
return {
'error': f'Command timed out after {timeout}s',
'command': ' '.join(cmd)
}
except FileNotFoundError:
return {
'error': 'dbt not found in PATH',
'suggestion': 'Install dbt: pip install dbt-core dbt-postgres'
}
except Exception as e:
logger.error(f"dbt command failed: {e}")
return {'error': str(e)}
async def dbt_parse(self) -> Dict:
"""
Validate dbt project without executing (pre-flight check).
Returns:
Dict with validation result and any errors
"""
result = self._run_dbt(['parse'])
# Check if _run_dbt returned an error (e.g., project not found, timeout, dbt not installed)
if 'error' in result:
return result
if not result.get('success'):
# Extract useful error info from stderr
stderr = result.get('stderr', '') or result.get('stdout', '')
errors = []
# Look for common dbt 1.9+ deprecation warnings
if 'deprecated' in stderr.lower():
errors.append({
'type': 'deprecation',
'message': 'Deprecated syntax found - check dbt 1.9+ migration guide'
})
# Look for compilation errors
if 'compilation error' in stderr.lower():
errors.append({
'type': 'compilation',
'message': 'SQL compilation error - check model syntax'
})
return {
'valid': False,
'errors': errors,
'details': stderr[:2000] if stderr else None,
'suggestion': 'Fix issues before running dbt models'
}
return {
'valid': True,
'message': 'dbt project validation passed'
}
async def dbt_run(
self,
select: Optional[str] = None,
exclude: Optional[str] = None,
full_refresh: bool = False
) -> Dict:
"""
Run dbt models with pre-validation.
Args:
select: Model selection (e.g., "model_name", "+model_name", "tag:daily")
exclude: Models to exclude
full_refresh: If True, rebuild incremental models
Returns:
Dict with run result
"""
# ALWAYS validate first
parse_result = await self.dbt_parse()
if not parse_result.get('valid'):
return {
'error': 'Pre-validation failed',
**parse_result
}
cmd = ['run']
if select:
cmd.extend(['--select', select])
if exclude:
cmd.extend(['--exclude', exclude])
if full_refresh:
cmd.append('--full-refresh')
return self._run_dbt(cmd)
async def dbt_test(
self,
select: Optional[str] = None,
exclude: Optional[str] = None
) -> Dict:
"""
Run dbt tests.
Args:
select: Test selection
exclude: Tests to exclude
Returns:
Dict with test results
"""
cmd = ['test']
if select:
cmd.extend(['--select', select])
if exclude:
cmd.extend(['--exclude', exclude])
return self._run_dbt(cmd)
async def dbt_build(
self,
select: Optional[str] = None,
exclude: Optional[str] = None,
full_refresh: bool = False
) -> Dict:
"""
Run dbt build (run + test) with pre-validation.
Args:
select: Model/test selection
exclude: Resources to exclude
full_refresh: If True, rebuild incremental models
Returns:
Dict with build result
"""
# ALWAYS validate first
parse_result = await self.dbt_parse()
if not parse_result.get('valid'):
return {
'error': 'Pre-validation failed',
**parse_result
}
cmd = ['build']
if select:
cmd.extend(['--select', select])
if exclude:
cmd.extend(['--exclude', exclude])
if full_refresh:
cmd.append('--full-refresh')
return self._run_dbt(cmd)
async def dbt_compile(
self,
select: Optional[str] = None
) -> Dict:
"""
Compile dbt models to SQL without executing.
Args:
select: Model selection
Returns:
Dict with compiled SQL info
"""
cmd = ['compile']
if select:
cmd.extend(['--select', select])
return self._run_dbt(cmd)
async def dbt_ls(
self,
select: Optional[str] = None,
resource_type: Optional[str] = None,
output: str = 'name'
) -> Dict:
"""
List dbt resources.
Args:
select: Resource selection
resource_type: Filter by type (model, test, seed, snapshot, source)
output: Output format ('name', 'path', 'json')
Returns:
Dict with list of resources
"""
cmd = ['ls', '--output', output]
if select:
cmd.extend(['--select', select])
if resource_type:
cmd.extend(['--resource-type', resource_type])
result = self._run_dbt(cmd)
if result.get('success') and result.get('stdout'):
lines = [l.strip() for l in result['stdout'].split('\n') if l.strip()]
result['resources'] = lines
result['count'] = len(lines)
return result
async def dbt_docs_generate(self) -> Dict:
"""
Generate dbt documentation.
Returns:
Dict with generation result
"""
result = self._run_dbt(['docs', 'generate'])
if result.get('success') and self.project_dir:
# Check for generated catalog
catalog_path = Path(self.project_dir) / 'target' / 'catalog.json'
manifest_path = Path(self.project_dir) / 'target' / 'manifest.json'
result['catalog_generated'] = catalog_path.exists()
result['manifest_generated'] = manifest_path.exists()
return result
async def dbt_lineage(self, model: str) -> Dict:
"""
Get model dependencies and lineage.
Args:
model: Model name to analyze
Returns:
Dict with upstream and downstream dependencies
"""
if not self.project_dir:
return {'error': 'dbt project not found'}
manifest_path = Path(self.project_dir) / 'target' / 'manifest.json'
# Generate manifest if not exists
if not manifest_path.exists():
compile_result = await self.dbt_compile(select=model)
if not compile_result.get('success'):
return {
'error': 'Failed to compile manifest',
'details': compile_result
}
if not manifest_path.exists():
return {
'error': 'Manifest not found',
'suggestion': 'Run dbt compile first'
}
try:
with open(manifest_path) as f:
manifest = json.load(f)
# Find the model node
model_key = None
for key in manifest.get('nodes', {}):
if key.endswith(f'.{model}') or manifest['nodes'][key].get('name') == model:
model_key = key
break
if not model_key:
return {
'error': f'Model not found: {model}',
'available_models': [
n.get('name') for n in manifest.get('nodes', {}).values()
if n.get('resource_type') == 'model'
][:20]
}
node = manifest['nodes'][model_key]
# Get upstream (depends_on)
upstream = node.get('depends_on', {}).get('nodes', [])
# Get downstream (find nodes that depend on this one)
downstream = []
for key, other_node in manifest.get('nodes', {}).items():
deps = other_node.get('depends_on', {}).get('nodes', [])
if model_key in deps:
downstream.append(key)
return {
'model': model,
'unique_id': model_key,
'materialization': node.get('config', {}).get('materialized'),
'schema': node.get('schema'),
'database': node.get('database'),
'upstream': upstream,
'downstream': downstream,
'description': node.get('description'),
'tags': node.get('tags', [])
}
except Exception as e:
logger.error(f"dbt_lineage failed: {e}")
return {'error': str(e)}