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NiclasOlofsson

DBT Core MCP Server

by NiclasOlofsson
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Python
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get_lineage

Retrieve the dependency tree for any dbt resource, showing upstream or downstream dependencies with configurable depth and auto-detection of resource type.

Instructions

Get lineage (dependency tree) for any dbt resource with auto-detection.

This unified tool works across all resource types (models, sources, seeds, snapshots, etc.) showing upstream and/or downstream dependencies with configurable depth.

Args: name: Resource name. For sources, use "source_name.table_name" or just "table_name" Examples: "customers", "jaffle_shop.orders", "raw_customers" resource_type: Optional filter to narrow search: - "model": Data transformation models - "source": External data sources - "seed": CSV reference data files - "snapshot": SCD Type 2 historical tables - "test": Data quality tests - "analysis": Ad-hoc analysis queries - None: Auto-detect (searches all types) direction: Lineage direction: - "upstream": Show where data comes from (parents) - "downstream": Show what depends on this resource (children) - "both": Show full lineage (default) depth: Maximum levels to traverse (None for unlimited) - depth=1: Immediate dependencies only - depth=2: Dependencies + their dependencies - None: Full dependency tree

Returns: Lineage information with upstream/downstream nodes and statistics. If multiple matches found, returns all matches for LLM to process.

Raises: ValueError: If resource not found or invalid direction

Examples: get_lineage("customers") -> auto-detect and show full lineage get_lineage("customers", "model", "upstream") -> where customers model gets data get_lineage("jaffle_shop.orders", "source", "downstream", 2) -> 2 levels of dependents

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
resource_typeNo
directionNoboth
depthNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations, but description details auto-detection, multiple match handling, error raising (ValueError), and depth limits. Does not mention read-only nature or auth, but these are implied. Sufficient behavioral context for safe use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with Args, Returns, Raises, Examples sections. Some redundancy (e.g., repeating parameter names), but front-loaded with core purpose. Slightly long but justified by complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, all parameters, return behavior (lineage info with stats, multiple matches), and errors. Output schema exists for return details, so omission is acceptable. Lacks pagination or performance notes, but complete for typical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description fully compensates: explains each parameter with examples, default values, and valid options (e.g., source naming format, direction options, depth meaning). Adds significant value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states 'Get lineage (dependency tree) for any dbt resource with auto-detection' – specific verb, resource, and scope. Clearly distinguishes from siblings like 'get_column_lineage' by focusing on resource-level, not column-level lineage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context on when to use (dependency queries), naming conventions for sources, and examples. However, lacks explicit guidance on when NOT to use or alternatives (e.g., use get_column_lineage for column lineage). Still clear overall.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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