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14 lines
1.0 KiB
TeX
14 lines
1.0 KiB
TeX
\section{Background and Related Work}
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\subsection{Agent Frameworks}
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LangChain~\cite{langchain2022} and AutoGPT~\cite{autogpt2023} pioneered the agent framework paradigm, providing abstractions for tool use and chain-of-thought reasoning. However, these frameworks face scalability challenges in production: LangChain's chain abstraction creates deep call stacks that complicate debugging, while AutoGPT's autonomous loop can lead to runaway token consumption.
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Recent work on multi-agent systems~\cite{multiagent2023} has explored specialized agent roles, but existing implementations lack formal mechanisms for context sharing and memory persistence across agent boundaries.
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\subsection{Model Context Protocol}
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The Model Context Protocol (MCP)~\cite{mcp2022} standardizes communication between AI models and external tools. MCP defines a JSON-RPC interface for tool discovery, invocation, and result handling. Our framework provides first-class MCP integration, allowing agents to discover and invoke tools dynamically.
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