Skip to main content
Glama
Sign In
mcp-lightcast

mcp-lightcast

by lawwu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Get Similarity Metadata

get_similarity_metadata
Read-onlyIdempotent

Discover available similarity models and the taxonomy versions each accepts, so you can choose compatible options for analysis.

Instructions

Discover Similarity models and the taxonomy versions they accept.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_similarity_metadata"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare read-only, idempotent, open-world, non-destructive behavior. The description adds the result scope (models and accepted taxonomy versions) but does not discuss auth, rate limits, pagination, or other operational traits; with rich annotations and an output schema, that is acceptable but modest.

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?

One compact sentence, front-loaded with the verb and resources; every word contributes and there is no boilerplate.

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?

For a zero-parameter read-only metadata tool with annotations and an output schema, the description identifies the discovered objects clearly. It could be stronger by connecting the metadata to query_similarity, but it is complete enough to call correctly.

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?

There are zero parameters, so the schema baseline is 4. The description appropriately adds no parameter details and does not need to.

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?

Names a specific verb ('Discover') and specific resources ('Similarity models and the taxonomy versions they accept'), making the tool's scope clear. It does not explicitly distinguish itself from query_similarity, but the metadata-versus-query distinction is inferable from the wording.

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

Usage Guidelines3/5

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

The verb 'Discover' implies that this tool is used to enumerate available Similarity models and accepted taxonomy versions, but it gives no explicit when-to-use guidance, prerequisites, or alternatives such as query_similarity. Routing between metadata discovery and similarity querying is left to the agent.

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

Deploy Server

Other Tools