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Updated: Aug 28, 2026

Operation of the Collaborative Composite Manufacturing (CCM) System
Published on: October 1, 2019
Coala: a standard-based framework for converting CWL-described command-line tools into agentic toolsets
Qiang Hu1, Qianqian Zhu1, Hong Zhang1
1Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA 14203.
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.
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