MCP Advisor

# Roadmap: The Future of MCP Advisor MCP Advisor is evolving from a simple recommendation system to an intelligent agent orchestration platform. Our vision is to create a system that not only recommends the right MCP servers but also learns from interactions and helps agents dynamically plan and execute complex tasks. ### Phase 1: Intelligence Layer (2025 Q2-Q3) #### Feedback Collection System - **User Feedback API**: Capture explicit feedback on MCP recommendations - **Implicit Feedback Tracking**: Monitor which MCPs are actually used after recommendation - **Success Metrics**: Track task completion rates with recommended MCPs - **A/B Testing Framework**: Compare different recommendation strategies #### Agent Interaction Analytics - **Interaction Logging**: Record detailed agent-MCP interactions - **Performance Metrics**: Measure response times, success rates, and error frequencies - **Conversation Analysis**: Extract patterns from agent-MCP conversations - **Cross-MCP Analytics**: Compare effectiveness across different MCP types #### Usage Pattern Recognition - **Task Classification**: Automatically categorize tasks that benefit from specific MCPs - **Query Intent Analysis**: Identify underlying intent beyond keyword matching - **Sequential Pattern Mining**: Discover common MCP usage sequences - **User Profiling**: Build profiles based on MCP usage patterns ### Phase 2: Learning Systems (2025 Q4 - 2026 Q1) #### Reinforcement Learning Framework - **State Representation**: Model the agent's context and task requirements - **Action Space**: Define MCP selection and configuration options - **Reward Function**: Design multi-objective rewards balancing accuracy, efficiency, and user satisfaction - **Policy Optimization**: Implement algorithms like PPO or SAC for policy learning #### Contextual Bandit Implementation - **Context Extraction**: Identify relevant features from queries and agent state - **Exploration Strategies**: Balance exploration vs. exploitation with Thompson sampling - **Online Learning**: Update models in real-time based on interaction outcomes - **Cold Start Handling**: Strategies for new MCPs with limited usage data #### Multi-Agent Reward Modeling - **Collaborative Rewards**: Design reward structures for multi-agent scenarios - **Preference Learning**: Learn from human preferences between different MCP selections - **Inverse Reinforcement Learning**: Infer reward functions from expert demonstrations - **Long-term Value Estimation**: Model delayed rewards for complex task chains ### Phase 3: Advanced Features (2026 Q1-Q2) #### Task Decomposition Engine - **Hierarchical Task Analysis**: Break complex tasks into subtasks - **MCP Capability Matching**: Map subtasks to appropriate MCPs - **Dependency Tracking**: Manage dependencies between subtasks - **Parallel Execution Planning**: Identify opportunities for concurrent MCP usage #### Dynamic Planning System - **Goal-Oriented Planning**: Generate plans to achieve specific objectives - **Adaptive Replanning**: Adjust plans based on intermediate results - **Resource Optimization**: Balance performance vs. cost in MCP selection - **Uncertainty Handling**: Plan robustly under incomplete information #### Adaptive MCP Orchestration - **Workflow Automation**: Create and execute multi-MCP workflows - **Context Preservation**: Maintain context across MCP transitions - **Failure Recovery**: Implement fallback strategies for MCP failures - **Performance Optimization**: Dynamically adjust MCP parameters based on feedback ### Phase 4: Ecosystem Expansion (2026 Q3-Q4) #### Developer SDK & API - **Custom Integration API**: Allow developers to integrate their own MCPs - **Analytics Dashboard**: Provide insights into MCP usage and performance - **Simulation Environment**: Test MCP orchestration in controlled environments - **Extension Framework**: Enable community-developed plugins #### Custom MCP Training Tools - **MCP Effectiveness Metrics**: Standardized evaluation framework - **Performance Benchmarking**: Compare MCPs against standard tasks - **Automated Testing**: Generate test cases for MCP validation - **Improvement Recommendations**: Suggest enhancements based on usage patterns #### Enterprise Integration Framework - **Security & Compliance**: Enterprise-grade security features - **Custom Deployment Options**: On-premise and private cloud deployment - **Team Collaboration**: Multi-user access and role management - **Integration with Enterprise Systems**: Connect with existing workflows and tools