ANSA API MCP Server

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search_ansa_api

Find ANSA Python API functions and code examples by searching documentation with natural language keywords in English or Chinese, with optional filtering by module or category.

Instructions

Search the ANSA Python API documentation.

Args: query: Search query (supports Chinese and English keywords) module: Filter by module name (e.g. "ansa.mesh", "ansa.base") category: Filter by category (e.g. "mesh_edit", "base_query") top_n: Maximum number of results to return (default 5)

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": "search_ansa_api"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes
`module`	No
`category`	No
`top_n`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0May 28, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It mentions keyword language support but does not disclose non-obvious behaviors like rate limits, pagination (only top_n count), or result format. Moderate transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with an Args section and is reasonably concise. However, it could be slightly shortened by removing the default value repetition for top_n (already in schema) without losing clarity.

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?

The parameter semantics are well-covered, but the description omits what the search returns (e.g., list of documentation sections, relevance scores). An output schema is present but not seen; assuming it covers return structure, the description still lacks context on search scope (e.g., full text vs title only).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description fully compensates. Each parameter is explained with examples (e.g., module: 'ansa.mesh', category: 'mesh_edit'), and top_n includes a default value. This adds significant meaning beyond the schema's type/title-only definitions.

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 'Search the ANSA Python API documentation' with a specific verb and resource, and includes details about keyword support. Although no sibling tools exist for differentiation, the purpose is unambiguous.

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?

No explicit guidance on when or when not to use this tool. With no sibling tools, the lack of alternatives context is less critical, but the description does not mention any prerequisites or ideal use cases, resulting in a neutral score.

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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