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Okareo MCP Server

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by okareo-ai
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Python
Remote

Get Target

get_target
Read-onlyIdempotent

Retrieve a target's current configuration by name. For custom endpoints, returns a clone-ready payload with redacted secrets that must be replaced before reuse.

Instructions

Check the current configuration of a test target.

    Retrieves a Target by name. Works for all target types (Generation,
    Custom Endpoint, and Voice).

    For **custom_endpoint** Targets, the response is a flat envelope whose
    keys mirror the kwargs accepted by `create_or_update_target`, so a
    copilot can read the result, swap in a new name + secrets, and feed it
    back to create to clone the Target. Fields the backend keeps secret
    (those listed in `sensitive_fields`) appear with the literal value
    `"***REDACTED***"` — these MUST be replaced with real values before
    calling `create_or_update_target`, which rejects payloads still
    containing the sentinel.

    The `max_parallel_requests` field on custom_endpoint Targets is the
    same setting the Okareo web UI labels "max concurrency".

    For generation and voice Targets, the response shape is unchanged
    (kept stable for existing callers).

    Args:
        name: Name of the target to retrieve.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.43

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations by revealing specific behavioral details: sensitive fields appear as '***REDACTED***' and must be replaced before create_or_update_target, the max_parallel_requests field matches the UI label 'max concurrency', and the response shape remains stable for generation/voice targets. These are valuable insights not derivable from annotations alone.

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 with a clear opening statement, followed by detailed but relevant caveats and an Args section. Every sentence adds value and the length is justified by the multi-target-type nuances and redaction behavior.

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?

Covers all target types, special handling for custom_endpoint, redacted fields, field naming mapping, and stability guarantees. With an output schema present, the description does not need to list return fields. It is highly complete for a read-only getter tool.

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?

The input schema has no property description (0% coverage), so the description compensates by stating 'name: Name of the target to retrieve.' This adds straightforward meaning to the single required parameter. Though minimal, it is sufficient for a simple string parameter.

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 clearly states the tool's function with a specific verb+resource: 'Check the current configuration of a test target' and 'Retrieves a Target by name.' It distinguishes itself from sibling tools like list_targets by indicating single-target retrieval by name and explicitly mentions support for all target types.

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 implies when to use the tool (when needing a single target's configuration) and provides context for different target types, but it does not explicitly contrast with list_targets or state exclusions. The intended use is clear enough from the phrasing and sibling tool names.

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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