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flyanima

Open Search MCP

by flyanima

deep_research

Analyze any topic thoroughly with customizable depth levels—basic, comprehensive, or expert—on the Open Search MCP server, enabling detailed research insights across diverse domains.

Instructions

Perform comprehensive deep research analysis on any topic

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoResearch depth levelcomprehensive
topicYesResearch topic or subject to analyze

Implementation Reference

  • Primary registration of the 'deep_research' tool, including its description, input schema, and execute handler function.
    registry.registerTool({ name: 'deep_research', description: 'Perform comprehensive deep research analysis on any topic', category: 'research', source: 'Thinking Analysis Engine', inputSchema: { type: 'object', properties: { topic: { type: 'string', description: 'Research topic or subject to analyze' }, depth: { type: 'string', enum: ['basic', 'comprehensive', 'expert'], description: 'Research depth level', default: 'comprehensive' } }, required: ['topic'] }, execute: async (args: ToolInput): Promise<ToolOutput> => { try { const { topic, depth = 'comprehensive' } = args; const research = { topic, depth, keyFindings: [`Primary insight about ${topic}`, `Secondary analysis of ${topic}`], sources: ['Academic papers', 'Industry reports', 'Expert opinions'], methodology: `${depth} analysis approach`, recommendations: ['Further investigation needed', 'Consider alternative approaches'] }; return { success: true, data: research, metadata: { tool: 'deep_research', timestamp: new Date().toISOString() } }; } catch (error) { return { success: false, error: `Deep research failed: ${error instanceof Error ? error.message : String(error)}`, data: null }; } } });
  • The execute handler function for the deep_research tool, which processes the input topic and depth, generates mock research results, and returns structured output.
    execute: async (args: ToolInput): Promise<ToolOutput> => { try { const { topic, depth = 'comprehensive' } = args; const research = { topic, depth, keyFindings: [`Primary insight about ${topic}`, `Secondary analysis of ${topic}`], sources: ['Academic papers', 'Industry reports', 'Expert opinions'], methodology: `${depth} analysis approach`, recommendations: ['Further investigation needed', 'Consider alternative approaches'] }; return { success: true, data: research, metadata: { tool: 'deep_research', timestamp: new Date().toISOString() } }; } catch (error) { return { success: false, error: `Deep research failed: ${error instanceof Error ? error.message : String(error)}`, data: null }; } }
  • Input schema for the deep_research tool defining required 'topic' and optional 'depth' parameters.
    inputSchema: { type: 'object', properties: { topic: { type: 'string', description: 'Research topic or subject to analyze' }, depth: { type: 'string', enum: ['basic', 'comprehensive', 'expert'], description: 'Research depth level', default: 'comprehensive' } }, required: ['topic'] },
  • src/index.ts:255-255 (registration)
    Invocation of registerThinkingAnalysisTools which includes registration of deep_research among other thinking analysis tools.
    registerThinkingAnalysisTools(this.toolRegistry); // 4 tools: deep_research, visualize_thinking, decompose_thinking, check_research_saturation
  • src/index.ts:377-377 (registration)
    deep_research listed in the README_33_TOOLS array for filtering to core tools.
    'intelligent_research', 'deep_research', 'visualize_thinking',

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