/**
 * MCP-LangChain Bridge
 *
 * Allows MCP to leverage LangChain capabilities while remaining in control.
 * LangChain becomes a tool that MCP uses, not the other way around.
 */
export interface LLMChainConfig {
    model: 'openai' | 'gemini' | 'claude';
    temperature?: number;
    maxTokens?: number;
    memory?: boolean;
}
export interface MCPLangChainTool {
    name: string;
    description: string;
    execute: (params: any) => Promise<any>;
}
/**
 * Bridge that allows MCP to use LangChain features as tools
 */
export declare class MCPLangChainBridge {
    private apiKeys;
    private chains;
    private memory;
    constructor(apiKeys: {
        openai?: string;
        gemini?: string;
        anthropic?: string;
    });
    /**
     * Initialize pre-configured chains
     */
    private initializeChains;
    /**
     * Execute a chain - called by MCP tools
     */
    executeChain(chainName: string, params: any): Promise<any>;
    /**
     * Create MCP tools that wrap LangChain functionality
     */
    createMCPTools(): MCPLangChainTool[];
    /**
     * Estimate cost for token usage
     */
    private estimateCost;
    /**
     * Create a custom chain dynamically
     */
    createCustomChain(config: {
        name: string;
        model: LLMChainConfig['model'];
        prompt: string;
        tools?: string[];
    }): Promise<void>;
}
/**
 * Integration example for MCP server
 */
export declare function integrateLangChainWithMCP(server: any, apiKeys: any): MCPLangChainBridge;
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