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Large language models (LLMs) struggle to effectively utilize a growing number of external tools, such as those defined by the Model Context Protocol (MCP)\cite{IntroducingMCP}, due to prompt bloat and selection complexity.
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.t., Rocktäschel, T., Riedel, S., Kiela, D.: Retrieval-augmented generation for knowledge-intensive nlp tasks. In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H. (eds.) Advances in Neural Information Processing Systems. vol. 33, pp. 9459–9474. Curran Associates, Inc. (2020), https://proceedings.neurips.cc/paper_files/paper/2020/file/6b493230205f780e1bc26945df7481e5-Paper.pdf
2020
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2022
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2023
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OpenAI: Chatgpt plugins (2023), https://openai.com/index/chatgpt-plugins
2023
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Schick, T., Dwivedi-Yu, J., Dessi, R., Raileanu, R., Lomeli, M., Hambro, E., Zettlemoyer, L., Cancedda, N., Scialom, T.: Toolformer: Language models can teach themselves to use tools. In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems. vol. 36, pp. 68539–68551. Curran Associates, Inc. (2023), https://proceedings.neurips.cc/paper_files/paper/2023/file/d842425e4bf79ba039352da0f658a906-Paper-Conference.pdf
2023
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Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K., Cao, Y.: React: Synergizing reasoning and acting in language models. International Conference on Learning Representations (ICLR) (2023), https://par.nsf.gov/biblio/10451467
2023
Cited alongside, same era.
Anthropic: Introducing the model context protocol (2024), https://www.anthropic.com/news/model-context-protocol
2024
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2024
Cited alongside, same era.
gkamradt: The needle in a haystack test (2024), https://github.com/gkamradt/LLMTest_NeedleInAHaystack
2024
Cited alongside, same era.
Patil, S.G., Zhang, T., Wang, X., Gonzalez, J.E.: Gorilla: Large language model connected with massive apis. Advances in Neural Information Processing Systems 37
2024
Later among the works it cites.
Blog, N.: What is retrieval -
2025
Closest in time.
2025
Closest in time.
ShipAny: Mcp servers (2025), https://mcp.so/
2025
Closest in time.
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2024
Cited alongside, same era.
OpenAI: Openai function calling, https://platform.openai.com/docs/guides/function-calling
Cited in the paper.