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mcp-adr-analysis-server

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MCP server for analyzing Architectural Decision Records and project architecture

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/** * Conversation Context Types * * Defines the structure for passing conversation context from calling LLMs * to the MCP server for context-aware analysis. */ export interface ConversationContext { /** Original human request text for context restoration */ humanRequest?: string; /** User's primary objectives from the conversation */ userGoals?: string[]; /** Specific areas of concern or interest */ focusAreas?: string[]; /** Limitations, compliance requirements, or restrictions */ constraints?: string[]; /** Relevant context from previous conversation */ previousContext?: string; /** Current project phase or stage */ projectPhase?: 'planning' | 'development' | 'migration' | 'production' | 'maintenance' | string; /** User's role or expertise level */ userRole?: 'architect' | 'developer' | 'manager' | 'ops' | 'security' | string; /** Specific requirements or preferences mentioned */ requirements?: string[]; /** Timeline or urgency information */ timeline?: string; /** Budget or resource constraints */ budget?: string; } /** * JSON Schema for conversation context - reusable across tools */ export declare const CONVERSATION_CONTEXT_SCHEMA: { type: "object"; description: string; properties: { humanRequest: { type: "string"; description: string; }; userGoals: { type: "array"; items: { type: "string"; }; description: string; }; focusAreas: { type: "array"; items: { type: "string"; }; description: string; }; constraints: { type: "array"; items: { type: "string"; }; description: string; }; previousContext: { type: "string"; description: string; }; projectPhase: { type: "string"; description: string; }; userRole: { type: "string"; description: string; }; requirements: { type: "array"; items: { type: "string"; }; description: string; }; timeline: { type: "string"; description: string; }; budget: { type: "string"; description: string; }; }; additionalProperties: boolean; }; /** * Utility function to extract context summary for prompts */ export declare function formatContextForPrompt(context?: ConversationContext): string; /** * Check if context contains meaningful information */ export declare function hasMeaningfulContext(context?: ConversationContext): boolean; //# sourceMappingURL=conversation-context.d.ts.map