Open Source LLM Tools
LLM tools help developers and organizations build, operate, and connect applications that use large language models. They address common needs such as producing structured outputs, serving models, giving agents access to external data or software, and automating repeatable workflows. By handling these tasks, they can make language model integrations more predictable and easier to incorporate into existing systems.
Open source options include libraries, command-line utilities, model-serving interfaces, agent capabilities, and connectors for APIs, operating systems, and other services. When choosing a tool, consider its maturity, license, maintenance activity, documentation, security practices, runtime requirements, and compatibility with your models and infrastructure. These tools are useful to developers, platform teams, and researchers building AI applications or automating software and operational tasks.
2 repositories · updated September 12, 2026

DeclarAgent: Declarative Runbook Executor for Safe AI Agent Workflows
DeclarAgent is an innovative declarative runbook executor specifically designed for AI agents. It enables agents to validate, dry-run, and safely execute multi-step YAML workflows. This tool provides a structured, auditable, and secure way for LLM agents to interact with real CLI workflows, enhancing their operational safety and reliability.

openapi-servers: Reference Implementations for LLM Tool Integration
The openapi-servers repository provides reference implementations for OpenAPI Tool Servers, simplifying the integration of external tools and data sources into LLM agents and workflows. By leveraging the OpenAPI specification, it ensures secure and easy communication without proprietary protocols. This project aims to accelerate the development of powerful AI applications by offering battle-tested, standard-compliant server examples.