Working with AI 🤖

Using Sling CLI with AI coding assistants like Claude Code

Sling CLI integrates seamlessly with AI coding assistants through the slingdata-ai plugin, enabling you to research APIs, design data integrations, and debug configurations using natural language—all within your AI assistant. See github repo https://github.com/slingdata-io/slingdata-ai for resources.

Overview

The slingdata-ai plugin provides:

• Slash commands for direct execution of replications and pipelines

• Specialized agents for complex workflows (API research, spec building, replication design)

• Skills that load contextual documentation automatically

• MCP integration that connects your AI assistant to Sling CLI tools

Supported AI Assistants:

• Claude Code (primary)

• GitHub Copilot

• Google Gemini

• Cline

• Other MCP-compatible assistants

Installation

From Marketplace (Recommended)

If using Claude Code with marketplace support:

/plugin marketplace add slingdata-io/slingdata-ai
/plugin install sling@slingdata-ai

Local Development

For contributing or local development:

claude --plugin-dir /path/to/slingdata-ai

Prerequisites

• Sling CLI v1.5.0+ must be installed

• Connections configured in ~/.sling/env.yaml

• AI assistant with MCP support

Install Sling CLI:

macOS

brew install slingdata-io/sling/sling

Linux

Windows

Quick Start

1. Configure a Connection

See the Environment documentation for details on managing connections.

sling conns set MY_POSTGRES type=postgres host=localhost user=postgres database=mydb

2. Use Commands in AI Assistant (Claude Code)

List connections:

/sling:conns list

Test a connection:

/sling:conns test MY_POSTGRES

Discover tables:

/sling:conns discover MY_POSTGRES public.*

3. Build with Natural Language

Instead of writing YAML manually, describe what you want:

Example: API Integration

"Research the Stripe API and create a specification for extracting customers and invoices"

The AI will:

1. Use the api-researcher agent to analyze Stripe's API documentation

2. Invoke api-spec-builder to create the YAML API specification

3. Use api-spec-tester to validate and debug

4. Generate a replication config to sync data to your database

Example: Database Replication

"Design a replication from MY_POSTGRES to MY_SNOWFLAKE that syncs the public.users and public.orders tables incrementally"

The AI will use the replication-builder agent to create a proper replication YAML with incremental settings.

Slash Commands (Claude Code)

Slash commands provide direct access to Sling CLI operations:

/sling:run

Execute a replication or pipeline file with validation.

Usage:

/sling:run /path/to/replication.yaml
/sling:run /path/to/pipeline.yaml

The command will:

• Parse and validate the YAML file

• Check connection availability

• Execute the replication or pipeline

• Display progress and results

/sling:conns

Manage connections interactively.

List all connections:

/sling:conns list

Test a connection:

/sling:conns test MY_POSTGRES

Discover streams (tables/files/endpoints):

/sling:conns discover MY_POSTGRES
/sling:conns discover MY_POSTGRES public.*
/sling:conns discover MY_S3 data/*.csv

Specialized Agents

Agents are AI sub-processes that handle complex, multi-step tasks autonomously. They have access to specific tools and are optimized for particular workflows.

API Specification Agents

Build custom REST API connectors through a research → build → test workflow.

api-researcher

Research REST API documentation to gather authentication methods, endpoints, pagination patterns, and rate limits.

Example:

"Use the api-researcher agent to analyze the Shopify Admin API documentation"

Outputs:

• Authentication type and credentials needed

• Available endpoints and their purposes

• Pagination strategy (cursor, offset, page-based)

• Rate limit information

api-spec-builder

Create Sling API specification YAML files from research findings.

Example:

"Build an API spec for Shopify with orders, customers, and products endpoints"

Outputs:

• Complete shopify.yaml specification

• Authentication configuration

• Endpoint definitions with pagination

• Response processors

Data Integration Agents

replication-builder

Design replication configurations for moving data between databases, files, and APIs.

Example:

"Create a replication from MY_POSTGRES to MY_SNOWFLAKE for the sales schema"

Outputs:

• Replication YAML with proper modes (full-refresh vs incremental)

• Stream selection and transformations

• Performance optimizations

pipeline-builder

Design multi-step data workflows with validation, transformations, and notifications.

Example:

"Create a pipeline that:
1. Syncs data from Stripe to Postgres
2. Runs a dbt transformation
3. Sends a Slack notification on completion"

Outputs:

• Pipeline YAML with sequential steps

• Hook configurations for notifications

• Error handling and retries

Skills

Skills are topic-specific documentation modules that load automatically based on keywords in your conversation. They provide contextual guidance without requiring explicit invocation.

Available Skills

Skill	Triggers	Purpose
sling	"sling", "data integration"	Platform overview and tools
sling-connections	"connection", "connect to"	Connection management
sling-replications	"replication", "sync", "copy"	Data movement configs
sling-pipelines	"pipeline", "workflow"	Multi-step orchestration
sling-transforms	"transform", "convert"	Data transformation functions
sling-hooks	"hook", "before", "after"	Pre/post actions
sling-troubleshooting	"error", "debug", "fix"	Error diagnosis
sling-api-specs	"api spec", "rest api"	API specification building

Example:

When you ask:

"How do I add a webhook notification after my replication completes?"

The sling-hooks skill automatically loads, providing context about:

• Hook types (http, sql, check, command)

• Placement options (pre/post replication)

• Configuration examples

• Variable access in hooks

Common Workflows

Building a Custom API Connector

Goal: Extract data from a REST API that Sling doesn't natively support. See the API Specifications concept guide for detailed information.

Steps:

1. Research the API

"Research the Zendesk API focusing on tickets, users, and organizations endpoints"

→ Uses api-researcher agent

1. Build the specification

"Create a Zendesk API spec with OAuth2 authentication and the endpoints we researched"

→ Uses api-spec-builder agent

1. Test the spec

/sling:conns set MY_ZENDESK type=api spec=zendesk secrets='{ client_id: xxx, client_secret: xxx }'
/sling:conns test MY_ZENDESK

→ Uses api-spec-tester agent if issues arise

1. Create replication

"Create a replication from MY_ZENDESK to MY_POSTGRES"

→ Uses replication-builder agent

1. Execute

/sling:run zendesk-replication.yaml

Database Migration

Goal: Migrate a database from Postgres to Snowflake. See database-to-database examples.

Steps:

1. Set up connections

/sling:conns test MY_POSTGRES
/sling:conns test MY_SNOWFLAKE

1. Design replication

"Create a replication from MY_POSTGRES to MY_SNOWFLAKE for all tables in the public schema with incremental sync where possible"

See replication modes and incremental examples.

1. Review and adjust The AI generates a replication YAML. You can refine:

"Exclude the public.logs table and use full-refresh for public.dim_products"

1. Execute

/sling:run pg-to-snowflake.yaml

ETL Pipeline with Validation

Goal: Build a pipeline that syncs data, validates it, and sends notifications. See pipeline examples.

Steps:

1. Describe the pipeline

"Create a pipeline that:
- Syncs Stripe charges to MY_POSTGRES
- Runs a SQL check that revenue is > 0
- Sends a Slack webhook on success
- Sends an email alert on failure"

1. Review generated YAML The pipeline-builder agent creates a pipeline with:

• Replication step

• SQL check hook

• HTTP webhook for Slack

• HTTP webhook for email alerts

1. Execute

/sling:run stripe-validation-pipeline.yaml

MCP Tools Reference

The plugin communicates with Sling CLI through Model Context Protocol (MCP) tools. These are invoked automatically by the AI but understanding them helps debug issues.

For detailed information about the MCP server, configuration options, and using Sling MCP with other AI assistants (Claude Desktop, VSCode Copilot, ChatGPT), see the MCP Server documentation.

connection

Manage connections (list, test, discover, set). See database connections, storage connections, and API connections.

Actions:

• list - Show all connections

• test - Test connection validity

• discover - List streams (tables/files/endpoints)

• set - Create or update connection

database

Query databases and retrieve metadata.

Actions:

• query - Execute SELECT queries

• get_schemata - Get schema/table/column metadata

• get_columns - Get column details

file_system

List, copy, and inspect files.

Actions:

• list - List files/directories

• copy - Copy between storage connections

• inspect - Get file metadata

replication

Manage replications.

Actions:

• parse - Validate YAML syntax

• compile - Full validation

• run - Execute replication

pipeline

Manage pipelines.

Actions:

• parse - Validate YAML syntax

• run - Execute pipeline

api_spec

Work with API specifications.

Actions:

• parse - Load and validate spec

• test - Test API endpoints

Troubleshooting

Plugin Not Loading

Check installation:

claude plugin list

You should see sling@slingdata-ai in the list.

Verify Sling CLI:

sling --version

Should return v1.5.0 or higher.

MCP Connection Issues

Check MCP server status: The plugin uses sling mcp as the MCP server. Test it:

sling mcp

Should start an MCP server on stdio.

Configuration location: .mcp.json in the plugin directory configures the server.

For more MCP troubleshooting: See the MCP Server troubleshooting section for log locations, debug output, and detailed diagnostics.

Commands Not Working

Check syntax:

# Correct
/sling:run /path/to/file.yaml

# Incorrect
/sling run /path/to/file.yaml  (missing colon)

Check file paths: Use absolute paths or paths relative to current working directory.

Agent Failures

Enable debug mode: When testing connections or API specs, add debug flag:

/sling:conns test MY_API --debug

Check credentials: Verify secrets in ~/.sling/env.yaml:

connections:
  MY_API:
    type: api
    spec: my_spec
    secrets:
      api_key: ${API_KEY}  # Must be set in environment

Review agent output: Agents provide detailed error messages. Look for:

• Authentication failures (401/403)

• Rate limit errors (429)

• Invalid endpoints (404)

• Malformed requests (400)

Best Practices

Use Natural Language First

Instead of manually writing YAML, describe what you want:

"Sync PostgreSQL users table to Snowflake incrementally using updated_at column"

The AI will generate proper configuration and explain design decisions.

Iterate with Agents

For complex tasks, work step-by-step with agents:

1. Research (api-researcher)

2. Cross-reference (api-cross-referencer)

3. Build (api-spec-builder)

4. Test (api-spec-tester)

Each agent focuses on its specialty, improving quality.

Use Skills for Learning

Skills auto-load based on keywords. To learn about a topic, ask questions:

"What transformation functions are available?"  → loads sling-transforms skill (see [Functions](../concepts/functions.md))
"How do I handle errors in pipelines?"          → loads sling-hooks skill (see [Hooks](../concepts/hooks.md))
"How do I set up OAuth2 for an API?"            → loads sling-api-specs skill (see [Authentication](../concepts/api/authentication.md))

What's Next?

• MCP Server - Use Sling with Claude Desktop, VSCode Copilot, and other AI assistants

• Environment Setup - Configure connections and credentials

• Replications - Deep dive into replication configs

• Pipelines - Build multi-step workflows

• API Specifications - Create custom API connectors

• Hooks - Add pre/post actions