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jonasliesas

singlestore-mcp-server

by jonasliesas

create_pipeline

Creates a SingleStore pipeline from a full CREATE PIPELINE statement for continuous loading from S3, Kafka, Azure, GCS, or filesystem. Pipeline is registered but not started; use start_pipeline.

Instructions

Create a new pipeline from a full CREATE PIPELINE statement.

Pipeline definitions vary a lot by source (S3, Kafka, Azure Blob, GCS,
filesystem, ...), format (CSV/JSON/Avro/Parquet) and optional transforms,
so this tool takes the complete statement text rather than trying to
model every variant as separate parameters. It only checks that the
statement actually starts with CREATE [OR REPLACE] PIPELINE before
running it. Creating a pipeline does not start it -- call start_pipeline
afterwards, or include FOREGROUND handling via start_pipeline.

Example create_pipeline_sql:
    CREATE PIPELINE my_pipeline AS
    LOAD DATA S3 's3://my-bucket/path/'
    CONFIG '{"region": "us-east-1"}'
    CREDENTIALS '{"aws_access_key_id": "...", "aws_secret_access_key": "..."}'
    INTO TABLE my_table
    FIELDS TERMINATED BY ',';

Args:
    create_pipeline_sql: The full CREATE PIPELINE ... statement.
    database: Database to create the pipeline in (defaults to the
        connection's configured database).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseNo
create_pipeline_sqlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It does so well by revealing that the tool only checks for the 'CREATE [OR REPLACE] PIPELINE' prefix before running, and that the pipeline is not started automatically. These are meaningful non-obvious behaviors beyond the basic 'create' action.

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

Conciseness5/5

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

The description is well-structured: it leads with the action, explains why the design is statement-based, states critical behavioral caveats, and includes a representative example. Every section serves a purpose and there is minimal redundancy.

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?

The description covers the tool's purpose, validation behavior, start semantics, and parameter meanings, and an output schema exists to describe return values. It does not mention error cases or permission requirements, but for this tool the provided context is sufficient for correct use and routing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It explains create_pipeline_sql as the full statement text, provides a concrete example, and clarifies that database defaults to the connection's configured database. This adds real meaning beyond the parameter names and types.

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?

The description opens with a specific verb and resource: 'Create a new pipeline from a full CREATE PIPELINE statement.' It clearly distinguishes this tool from siblings like start_pipeline, drop_pipeline, and alter_pipeline by focusing on creation from a complete statement.

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?

It explicitly tells the agent that creating a pipeline does not start it, and directs it to call start_pipeline afterwards. It also explains why the tool takes a full statement rather than structured parameters, which gives context for when it is appropriate. It does not state when not to use alternatives like run_sql, but the guidance is clear enough.

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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