Coala: a standard-based framework for converting CWL-described command-line tools into agentic toolsets

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ID: 326474
2026
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Abstract
Abstract Summary Large Language Models (LLM) can orchestrate computational analyses through agentic systems, but scaling their toolsets remains a barrier because tool definitions are often hard coded into agent implementation. We developed Command-line LLM-agent Adapter (Coala), a standards-based framework that bridges the Model Context Protocol (MCP) and the Common Workflow Language (CWL). Coala turns CWL tool descriptions into MCP-compatible, LLM-accessible schemas, treating tool definitions as data rather than code. Tools are then executed in containerized environments through a generic MCP server, which separates the agent’s reasoning from tool execution. This framework improves reproducibility, reduces ongoing maintenance burden, and enables interactive access to local command-line tools through natural-language queries. Availability and Implementation Coala is available at https://coala.info and is openly developed on GitHub: https://github.com/coala-info/coala. Supplementary information Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7204267335 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Qiang Hu, Qianqian Zhu, Hong Zhang, Tao Liu, Song Liu
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Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag641
URL
https://doi.org/10.1093/bioinformatics/btag641
Keywords Keywords not found

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