dbt Cloud MCP Server (Official)
Official dbt Cloud MCP server enabling AI agents to interact with dbt's analytics engineering platform — querying model metadata, running dbt jobs, checking job status, exploring data lineage, and managing dbt Cloud environments.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
HTTPS enforced. Service tokens with project-level scopes. SOC 2 Type II, GDPR. Good analytics platform security.
⚡ Reliability
Best When
An agent needs to interact with dbt models, run transformations, or query the semantic layer in a dbt Cloud environment.
Avoid When
You're using Spark, Flink, or other non-SQL transformation tools.
Use Cases
- • Querying dbt model metadata and data lineage from analytics agents
- • Triggering dbt jobs for pipeline orchestration from agents
- • Checking dbt job run status and failure analysis
- • Exploring semantic layer definitions for AI-driven data querying
- • Validating dbt model dependencies before deployment
Not For
- • Teams not using dbt for data transformation
- • Direct database operations (use database-specific MCPs for that)
- • Non-SQL data transformation workflows
Interface
Authentication
Service tokens with account, project, or job-level permission scopes. Personal API tokens for individual access. Service tokens recommended for agents.
Pricing
dbt Core is free open source. dbt Cloud adds managed runs, CI/CD, documentation. API access on Team and Enterprise.
Agent Metadata
Known Gotchas
- ⚠ Account ID + project ID required for most operations — configure both
- ⚠ Job runs are async — agents must poll for completion
- ⚠ dbt semantic layer requires separate configuration and understanding of metrics
- ⚠ API v2 vs v3 endpoints have different capabilities — check version compatibility
- ⚠ Model and job IDs are numeric — agents must discover IDs before operating
- ⚠ Service token permission scopes control what operations are allowed per project
Alternatives
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Scores are editorial opinions as of 2026-03-07.