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Agent Knowledge MCP

prompt_server.py2.28 kB
""" AgentKnowledgeMCP Prompt Server FastMCP server for prompts providing comprehensive MCP usage guide content for LLM assistance. Modular Architecture: - Mounts specialized sub-servers for specific functionality - Smart prompting capabilities via dedicated sub-server - Unified interface for all prompt-related tools Sub-servers: - smart_prompting_server.py: 1 tool (ask_mcp_advice) for AI-filtered project guidance - instructions_server.py: 2 prompts (mcp_usage_guide, copilot_instructions) for guidance documentation """ from fastmcp import FastMCP # Import sub-server applications for mounting from .sub_servers.smart_prompting_server import app as smart_prompting_app from .sub_servers.instructions_server import app as instructions_app # Create FastMCP app for prompt guidance and resource access app = FastMCP( name="AgentKnowledgeMCP-Prompts", version="2.0.0", instructions="Unified prompt server with comprehensive MCP usage guides and modular smart prompting capabilities" ) # ================================ # SERVER MOUNTING - MODULAR ARCHITECTURE # ================================ print("🏗️ Mounting Prompt sub-servers...") # Mount smart prompting sub-server app.mount(smart_prompting_app) # 1 tool: ask_mcp_advice for AI-filtered guidance # Mount instructions sub-server app.mount(instructions_app) # 2 prompts: mcp_usage_guide, copilot_instructions print("✅ Smart prompting sub-server mounted successfully") print("✅ Instructions sub-server mounted successfully") # ================================ # CLI ENTRY POINT # ================================ def cli_main(): """CLI entry point for Prompt FastMCP server.""" print("🚀 Starting AgentKnowledgeMCP Prompt FastMCP server...") print("📝 Available prompts (via sub-servers):") print(" • mcp_usage_guide - Comprehensive usage guide with scenarios and tutorials") print(" • copilot_instructions - AI assistant behavioral guidelines and protocols") print("🛠️ Available tools (via sub-servers):") print(" • ask_mcp_advice - Smart prompting with AI-filtered project knowledge") print("✨ Provides complete guidance and modular smart prompting capabilities") app.run() if __name__ == "__main__": cli_main()

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