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apache-atlas-mcp

apache-atlas-mcp

by DanMeon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

quick_search

Search entities across types using partial names. Filter by type and limit results for autocomplete-style lookups.

Instructions

Perform a quick search across all entity types.

Faster than basic search, optimized for autocomplete-style lookups. Good for finding entities when you have a partial name.

Args: query: Search text (supports partial matching). type_name: Optional type filter (e.g., "hive_table"). limit: Maximum number of results (default: 25).

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": {
      "query": "<query>"
    },
    "name": "quick_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
type_nameNo
limitNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4/5.0
Behavior2/5

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

No annotations provided, so the description carries full burden. It only mentions speed and partial matching, but fails to disclose any behavioral traits like whether the operation is read-only, destructive, or requires authentication. No mention of side effects or limitations.

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?

Highly concise: one-line purpose, one sentence for use case, then bulleted parameter descriptions. Front-loaded with essential info, no unnecessary words. Every sentence adds value.

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?

Has output schema (signal indicates true), so return value details are covered. Description covers basic functionality, parameter semantics, and use case. Lacks info on sorting or pagination, but acceptable for a quick search tool given the output schema.

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?

Schema description coverage is 0%, yet the description includes an Args section that explains each parameter: query (supports partial matching), type_name (optional type filter), limit (default 25). This adds meaningful context beyond the raw schema types and defaults.

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 'Perform a quick search across all entity types' and adds 'Faster than basic search, optimized for autocomplete-style lookups.' This distinguishes it from sibling tools like search_entities or dsl_search by emphasizing speed and partial matching.

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?

Provides explicit context: 'Faster than basic search' and 'optimized for autocomplete-style lookups' and 'Good for finding entities when you have a partial name.' It implies when to use vs a basic search, but doesn't name specific sibling alternatives. Clear enough for usage decisions.

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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