A
licenseNot graded
qualityD
maintenanceEnables AI agents to query live schema, lineage, and query-context across data warehouses, dbt projects, orchestration systems, and BI tools via MCP tools.
Apache 2.0
dlt
Officialby dlt-hub
Allows storing and querying dlt pipeline data in DuckDB, enabling SQL analysis and schema management for DuckDB destinations.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@dlt Show me the tables and schema of the 'taxi' pipeline"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
How is it useful?
Large language models (LLMs) know a lot about the world, but nothing about your specific code and data.
The Model Context Protocol (MCP) server allows the LLM to retrieve up-to-date and correct information about your dlt pipelines, datasets, schema, etc. This significantly improves the development experience in AI-enabled IDEs (Copilot, Cursor, Continue, Claude Code, etc.)
Related MCP server: dbt-assay
Installation
The package manager uv is required to launch the MCP server.
Add this section to your MCP configuration file inside your IDE. Add your destination(s) in the extras dlt-mcp[...]
{
"name": "dlt",
"command": "uv",
"args": [
"run",
"--with",
"dlt-mcp[duckdb]",
"dlt-mcp",
],
}NOTE
The configuration file format varies slightly across IDEs
Features
Tools
The dlt MCP server provides tools that allows the LLM to take actions:
list_pipelines: Lists all available dlt pipelines. Each pipeline consists of several tables.
list_tables: Retrieves a list of all tables in the specified pipeline.
get_table_schemas: Returns the schema of the specified tables.
execute_sql_query: Executes a SELECT SQL statement for simple data analysis.
get_load_table: Retrieves metadata about data loaded with dlt.
get_pipeline_local_state: Fetches the state information of the pipeline, including incremental dates, resource state, and source state.
get_table_schema_diff: Compares the current schema of a table with another version and provides a diff.
search_docs: Searches over the
dltdocumentation using different modes (hybrid, full_text, or vector) to verify features and identify recommended patterns.search_code: Searches the source code for the specified query and optional file path, providing insights into internal code structures and patterns.
Available Tools
8 toolsdisplay_schemaB
Generate a mermaid diagram to represent the pipeline schema
pipeline_name: name of the pipeline hide_columns: when True, the columns are hidden
Inputs: pipeline_name (required), hide_columns. Returns: result
execute_sql_queryD
Inputs: pipeline_name (required), sql_select_query (required). Returns: result
get_load_tableC
Retrieve metadata about data loaded with dlt.
Inputs: pipeline_name (required). Returns: result
get_pipeline_local_stateC
Retrieve the pipeline state information. Includes: incremental dates, resource state, source state
Inputs: pipeline_name (required). Returns: Schema for a pipeline state that is stored within the pipeline working directory
get_table_schemaC
Get the schema of the specified table.
Inputs: pipeline_name (required), table_name (required). Returns: TypedDict that defines properties of a table
get_table_schema_diffC
Get the diff between schema versions of a table.
Inputs: pipeline_name (required), table_name (required), another_version_hash. Returns: result
list_pipelinesB
List all available dlt pipelines. Each pipeline has several tables.
Inputs: no named parameters. Returns: result
list_tablesB
List all available tables in the specified pipeline.
Inputs: pipeline_name (required). Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
C2.8/5.0
Scored across 8 tools
Disambiguation5/5
Each tool has a distinct purpose: display_schema for diagram, execute_sql_query for running SQL, get_load_table for load metadata, get_pipeline_local_state for state, get_table_schema for schema, get_table_schema_diff for version diff, list_pipelines for pipeline listing, list_tables for table listing. No overlap.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case (e.g., display_schema, get_table_schema, list_pipelines). No mixing of conventions.
Tool Count5/5
With 8 tools covering pipeline inspection, schema viewing, state retrieval, and query execution, the count is well-scoped for a data pipeline management server.
Completeness4/5
The tool set covers inspection and querying comprehensively (list, schema, state, load info, SQL execution), but lacks lifecycle operations like creating or deleting pipelines, which may be intentional for a read-only server.
Maintenance
ActivityInactive
ResponsivenessNo recent community issues
Related MCP Connectors
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Publish your API docs so AI assistants can look up endpoints and call your API correctly.
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