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mcp_ollama_list

Retrieve a list of available Ollama models on the Ontology MCP server to facilitate AI-driven ontology data queries and manipulations.

Instructions

사용 가능한 Ollama 모델 목록을 조회합니다

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler for 'mcp_ollama_list' that delegates to ollamaService.listModels() and formats the response.
    async handler(args: any): Promise<ToolResponse> {
      const result = await ollamaService.listModels();
      return {
        content: [
          {
            type: 'text' as const,
            text: result
          }
        ]
      };
  • Input schema for mcp_ollama_list tool (no parameters required).
    inputSchema: {
      type: 'object',
      properties: {}
    },
  • src/index.ts:34-34 (registration)
    Tool capability registration in MCP server capabilities.
    mcp_ollama_list: true,
  • Core implementation of model listing via Ollama /api/tags endpoint.
    async listModels(): Promise<string> {
      try {
        const response = await axios.get(this.getApiUrl('tags'));
        return JSON.stringify(response.data, null, 2);
      } catch (error) {
        throw new McpError(ErrorCode.InternalError, `모델 목록을 가져오는데 실패했습니다: ${formatError(error)}`);
      }
    }
  • Full tool registration object including name, description, schema, and handler in the exported tools array.
    {
      name: 'mcp_ollama_list',
      description: '사용 가능한 Ollama 모델 목록을 조회합니다',
      inputSchema: {
        type: 'object',
        properties: {}
      },
      async handler(args: any): Promise<ToolResponse> {
        const result = await ollamaService.listModels();
        return {
          content: [
            {
              type: 'text' as const,
              text: result
            }
          ]
        };
      }
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states this is a retrieval operation ('조회합니다'), implying it's likely read-only, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what format the output takes. For a tool with zero annotation coverage, this is insufficient.

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?

The description is a single, efficient sentence in Korean that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 (0 parameters, no output schema) and lack of annotations, the description is minimally adequate but has clear gaps. It explains what the tool does but misses behavioral context and usage guidelines, which are important for an agent to operate effectively in a server with many sibling tools.

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?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter information, and it appropriately doesn't mention any. Baseline is 4 for tools with no parameters.

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 the verb ('조회합니다' - retrieve/list) and resource ('Ollama 모델 목록' - Ollama model list), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'mcp_ollama_show' or 'mcp_ollama_status', which might also provide model-related information.

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 is provided on when to use this tool versus alternatives. With siblings like 'mcp_ollama_show' (which might show details of a specific model) and 'mcp_ollama_status' (which might show system status), the description lacks context on use cases, prerequisites, 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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