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46 lines (40 loc) · 1.38 KB
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cff-version: "1.2.0"
message: "If you use this software, please cite it as below."
type: software
title: "MCPStack"
abstract: "Stack & Orchestrate MCP Tools — The Scikit-Learn-Pipeline Way , For LLMs"
version: "0.0.1"
date-released: "2025-08-20"
license: "MIT"
repository-code: "https://github.com/MCP-Pipeline/MCPStack"
url: "https://github.com/MCP-Pipeline"
keywords:
- "MCP"
- "LLM"
- "Machine Learning"
- "Pipeline"
- "Scikit-Learn"
- "Orchestration"
authors:
- given-names: "Simon"
family-names: "Provost"
affiliation: "University of Kent"
email: "simon.gilbert.provost@gmail.com"
orcid: "https://orcid.org/0000-0001-8402-5464"
contact:
- given-names: "Simon"
family-names: "Provost"
email: "simon.gilbert.provost@gmail.com"
preferred-citation:
type: software
title: "MCPStack: Stack & Orchestrate MCP Tools — The Scikit-Learn-Pipeline Way, For LLMs"
version: "0.0.1"
url: "https://github.com/MCP-Pipeline/MCPStack"
authors:
- family-names: "Provost"
given-names: "Simon"
orcid: "https://orcid.org/0000-0001-8402-5464"
notes: >
We thank the M3’s MCP initial work from @rafiattrach, @rajna-fani, @MoreiraP12 for inspiration and which made our
contributions to the MCPStack project. Innovations on top of M3 in this project include the use of
Scikit-Learn-style pipelines for MCP tools rather than transformers / estimators.