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Algenta MCP Server

by io.github.thyn-ai
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test_connector

Idempotent

Run a real connectivity test against one saved connector's stored config and persist the outcome as its live or error status with last_tested_at. This opens an actual connection to the source. Use preview_test_connector for an unsaved inline definition, and browse_connector once the connector is live. Returns success, message, latency_ms, status, error_type, and recoverable.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "connector_id": "<connector_id>"
    },
    "name": "test_connector"
  }
}

Input Schema

NameRequiredDescriptionDefault
connector_idYesSaved connector id from list_connectors.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / connector_id / description
      Added value: +"Saved connector id from list_connectors."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations cover readOnly/idempotent/destructive hints, but the description adds valuable behavior beyond them: it persists the outcome as live or error status, records last_tested_at, and returns latency/error details. It clearly discloses the real-connection side effect. No contradiction with 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?

Three tight sentences: purpose and side effect first, alternative routing second, return payload last. There is no filler, and every sentence contributes either selection guidance or invocation context.

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?

For a one-parameter tool with no output schema, the description tells the agent what the tool does, when to use it versus alternatives, what effect it has, and what the response will contain. Nothing critical is missing for correct selection and invocation.

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 coverage is 100% for connector_id, and the schema already explains the parameter. The description adds a bit of context by mentioning 'saved connector's stored config' and implicitly linking to list_connectors, but the schema carries the main semantic load.

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 states a specific verb and resource: 'Run a real connectivity test against one saved connector's stored config' and distinguishes it from preview_test_connector and browse_connector. An agent can immediately tell what this tool does and how it differs from nearby siblings.

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?

The description explicitly routes usage: use preview_test_connector for an unsaved inline definition, and browse_connector once the connector is live. It also calls out that this 'opens an actual connection to the source,' which is important context for deciding whether to invoke it.

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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