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getsimba-ai

Simba MCP Server

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by getsimba-ai

List Pipelines

list_pipelines
Read-onlyIdempotent

Retrieve a list of your data pipelines, sorted by most recent update. Each entry includes the pipeline ID, version count, and latest version details. Use the version ID as a pipeline_version_id for other operations.

Instructions

List the data pipelines this key's owner has, most recently updated first, each with id, pipeline_hash, name, description, version_count and latest_version (id, version, created_at, row_count, checksum). Identity only: no definitions, parameters or output data. Use a version id as pipeline_version_id in get_recipe_draft_template. Requires the ingest scope; the same ownership rule as the app. Paging is opt-in: pass limit (1-200) to receive a page and next_cursor; send that cursor back unchanged for the next page; null next_cursor means the end.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
cursorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.1

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds substantial behavioral detail: ordering (most recently updated first), content exclusions (identity only), auth requirement (ingest scope), and a full explanation of opt-in pagination (limit range, cursor semantics, null termination). This goes well beyond the annotations.

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 and front-loaded with the core purpose. Every sentence adds necessary information—scope, fields, ordering, auth, paging—with no fluff. It is appropriately sized for the complexity of the tool.

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

Completeness5/5

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

Given the output schema exists and the description explicitly lists the returned fields (id, pipeline_hash, name, etc.), the description covers everything an agent needs: purpose, prerequisites, pagination, and output structure. Nothing critical is missing.

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 the description carries the full burden. It clearly explains both parameters: limit (1-200) triggers paging, and cursor must be sent back unchanged for the next page. This provides complete meaning beyond the bare schema.

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

Purpose4/5

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

The description clearly states the verb 'list' and the resource 'data pipelines' with specific fields returned and ordering. It does not explicitly differentiate from sibling tools like list_pipeline_versions, though the resource name and 'Identity only' scope imply a distinction. This meets the 'clear but no sibling differentiation' criterion.

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

Usage Guidelines3/5

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

The description provides usage context: requires the ingest scope, same ownership rule as the app, and mentions how to use the result (version id as pipeline_version_id). It does not explicitly state when not to use this tool or name alternatives, so the guidance is implied rather than explicit.

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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