PulseGatePost-LLM software, agents & workflows market (since 2022)
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  2. llmdoctor/
  3. Alternatives

llmdoctor Alternatives

Find LLM cost leaks before your bill does. Static analysis for Anthropic and OpenAI client code. Below are 9 other dev tools apps with similar functionality to llmdoctor, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.

  • llmdog
    pypi.org

    llmdog is an open-source, lightweight command-line tool and Python library that enables developers to interact with any API endpoint compatible with OpenAI Chat Completions. It is suitable for developers building or testing LLM-based applications.

  • llms-py
    github.com

    A lightweight CLI tool and OpenAI-compatible server for querying multiple Large Language Model (LLM) providers

  • llmleaks
    github.com

    Security tool for detecting exposed LLM/AI API keys in public repositories

  • llm-org-cost-monitor
    pypi.org

    llm-org-cost-monitor is an open-source command-line tool that helps organizations generate detailed cost and usage reports for OpenAI and Anthropic APIs. It is designed for developers and administrators who need to monitor and manage their AI API expenses efficiently. The tool provides clear insights into organizational spending and usage patterns.

  • llmprices
    github.com

    Compare LLM API costs across providers from the command line

  • vllm-doctor
    github.com

    vllm-doctor is an open-source command-line tool for diagnosing and troubleshooting vLLM inference servers. It provides diagnostics and Prometheus integration, helping AI infrastructure engineers maintain reliable deployments.

  • llmcode-cli
    github.com

    Open-source AI agent runtime for any LLM — production-grade coding agent with multi-layer memory, multi-agent orchestration, and defense-in-depth security

  • open-batch-llm
    github.com

    A CLI tool to manage batch LLM calls

  • LLM Armor
    llmarmor.dev

    LLM Armor is an open-source CLI tool that performs static analysis on Python codebases for AI applications, focusing on the OWASP LLM Top 10 security risks. It helps developers identify vulnerabilities such as prompt injection and sensitive data exposure before attackers can exploit them. Designed for integration into CI/CD pipelines, it runs quickly and offline, making it ideal for AI developers and security teams.