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List Connections

list_connections
Read-onlyIdempotent

List saved Markifact connections for an app/platform.

A connection is a saved authenticated integration in Markifact. The returned id is the connection_id used to choose which saved login/integration an operation should use.

Important:

  • connection_id is not an external platform account ID.

  • External account IDs, customer IDs, property IDs, and similar values are separate operation inputs.

  • One connection may have access to multiple external accounts.

    • In most cases, you don not need to provide connection_id. If the user has only one connected login for a platform in their workspace, operations usually use that connection automatically. Use this tool only when the user wants a specific saved integration or has multiple connections for the same platform.

Returns JSON with available connections containing id, type, and display_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connection_typeNoOptional app/platform filter. Examples: 'gads', 'ga4', 'meta_ads', 'hubspot', 'slack'. Leave empty to list all available connections.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower, yet the description adds real semantics: connection_id is not an external platform account ID, external account/customer/property IDs are separate operation inputs, and one connection can span multiple external accounts. That is behavioral context an agent cannot get from the structured fields.

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?

Front-loaded with the core purpose, then cleanly bulleted into the important disambiguation and the when-to-use rule. It runs slightly long and contains a typo ('you don not need'), but nearly every sentence carries distinct meaning.

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?

With an output schema present, the description needn't explain return shape, and it still names the relevant fields it returns ('id', 'type', 'display_name'). Combined with full annotation coverage and a fully described parameter, nothing an agent needs to call this correctly is missing.

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 100% and the single parameter already documents itself with examples ('gads', 'ga4', 'meta_ads') and the leave-empty behavior, so the schema does the heavy lifting. The description reinforces the app/platform filtering concept but adds no syntax or format detail beyond the schema, making the baseline 3 appropriate.

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?

States a specific verb and resource ('List saved Markifact connections') and goes further by defining what a connection is ('a saved authenticated integration') and what the returned id is for. An agent can distinguish this from operation-running siblings like run_operation or find_operations without opening any schema.

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

Usage Guidelines5/5

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

Explicitly states the negative case first ('In most cases, you do not need to provide connection_id... operations usually use that connection automatically') and then the positive trigger ('Use this tool only when the user wants a specific saved integration or has multiple connections for the same platform'). This is textbook when-to-use / when-not-to-use guidance.

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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