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scalekit-inc

Scalekit MCP Server

Official

search_connectors

Search the Scalekit connector catalog for an environment to find connectors by keyword, filter by type, and check setup status.

Instructions

Search the connector catalog (e.g. Google, Notion, Slack) for the given environment. Returns matching connectors with their identifier, category, and type. When includeSetupStatus is true, each result is annotated with whether the connector has been set up in the environment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSearch keyword to match against connector name, identifier, description, or categories (e.g. "gmail", "slack", "hubspot").
pageSizeNo
pageTokenNoOpaque token from a previous response to fetch the next page.
connectorTypeNoFilter by connector type: SCALEKIT (pre-built connectors provided and maintained by Scalekit, shared across all environments), CUSTOM (connectors created by environment users, scoped to a single environment and not shared between environments), or ALL (both types).ALL
environmentIdYes
includeSetupStatusNoWhen true, also checks which connectors have been set up (have active connections) in the environment.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It discloses the returned fields and the conditional effect of includeSetupStatus, which is useful. However, it does not mention pagination behavior, the fact that omitting query returns all connectors, or the subtle scoping difference between SCALEKIT and CUSTOM connectors.

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?

Three short sentences, each earning its place: purpose with examples, return shape, and conditional behavior. The most useful information is front-loaded and there is no filler.

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 core return values and the conditional annotation behavior despite the absence of an output schema. It does not explicitly mention pagination or optional-query list-all behavior, but the schema documents pageToken and required parameters well enough. This is mostly complete for a 6-parameter search tool.

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

Parameters3/5

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

Schema description coverage is 67%, so the schema still does meaningful work. The description adds search examples and clarifies includeSetupStatus behavior, but it does not compensate for the undocumented pageSize bounds or environmentId format. This is an adequate but not exceptional contribution.

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 names a specific verb and resource: 'Search the connector catalog' with concrete examples (Google, Notion, Slack). It clearly scopes the operation to a given environment and lists the returned fields (identifier, category, type), which distinguishes it from sibling search_tools and search_docs.

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?

The description establishes a clear context: use this when you need to find connectors available in an environment. It does not explicitly name alternative tools or state exclusions, which prevents a 5, but it gives enough context for an agent to infer when this tool is appropriate.

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