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MCP server for AI agents with RAG, hierarchical memory, and tools.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "A-Modular-Kingdom" yet — see the docs or source repo.
Use A-Modular-Kingdom to configure RAG retrieval for my AI agent, connect this set of product documents, and design a workflow that searches first and then answers user questions.
A knowledge base integration plan, RAG workflow steps, and configuration guidance for document-grounded answers.
Using A-Modular-Kingdom’s hierarchical memory, design short-term context, long-term memory, and preference storage for a customer support AI agent, and explain the calling logic.
A hierarchical memory structure, data retention strategy, and methods for reading and updating memory across conversations.
Based on the 8+ tools provided by A-Modular-Kingdom, design an automated agent workflow that receives tasks, retrieves information, stores memory, calls tools, and produces final results.
A multi-tool orchestration plan, step responsibilities, tool invocation order, and overall execution logic.
Expose modular retrieval and reasoning tools to AI assistants through MCP.
Turn unstructured documents into a searchable knowledge base for AI agents.
Build modular RAG workflows for document Q&A, semantic search, and knowledge bases.
Build production-grade RAG systems with hybrid retrieval and agentic reasoning.
Intelligent RAG tool that chooses between private knowledge and web search.
Centralize memory, tools, and logic for leaner prompts and scalable AI agents.