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MCP Gemini Server

MCP Gemini Server

by bsmi021
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

exampleTool

Generate personalized greeting messages by inputting a name and selecting a language. The tool on MCP Gemini Server uses structured input parameters to deliver tailored outputs for various use cases.

Instructions

An example tool that takes a name and returns a greeting message. Demonstrates the basic structure of an MCP tool using Zod for parameter definition.

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": {
      "name": "<name>"
    },
    "name": "exampleTool"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoOptional language code for the greeting (e.g., 'en', 'es', 'fr'). Defaults to 'en' if not provided or invalid.
nameYesThe name to include in the greeting message. Required, 1-50 characters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the tool returns a greeting message, but doesn't disclose behavioral traits like error handling, rate limits, authentication needs, or what happens with invalid inputs. The description adds minimal context beyond the basic operation.

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?

Two sentences, zero waste. The first sentence states the purpose clearly, and the second provides meta-context about being an example. Every sentence earns its place with no redundancy.

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

Completeness3/5

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

Given the tool's low complexity (simple greeting generator), no annotations, no output schema, and high schema coverage, the description is adequate but minimal. It covers the basic operation but lacks details on return format or error behavior that would be helpful for an agent.

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%, so the schema already documents both parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema, meeting the baseline for high coverage without extra value.

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 what the tool does ('takes a name and returns a greeting message') with a specific verb ('returns') and resource ('greeting message'). It distinguishes from sibling tools by being a simple greeting generator rather than Gemini-related operations, though it doesn't explicitly contrast with siblings.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives is provided. The description mentions it 'demonstrates the basic structure of an MCP tool,' which implies educational/example usage, but doesn't specify practical contexts or exclusions.

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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