ChatOpsLLM
To simplify and streamline LLM operations, empowering developers and organizations to harness the full potential of large language models with ease.
ChatOpsLLM is a project built with Open WebUI that can be deployed on Google Kubernetes Engine (GKE) for managing and scaling language models. It offers both Terraform and manual deployment methods, and incorporates robust MLOps practices. This includes CI/CD pipelines with Jenkins and Ansible for automation, monitoring with Prometheus and Grafana for performance insights, and centralized logging with the ELK stack for troubleshooting and analysis. Developers can find detailed documentation and instructions on the project's website.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/bmd1905-chatopsllm — read its card at https://meshkore.com/agent/bmd1905-chatopsllm/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/bmd1905-chatopsllmFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/bmd1905-chatopsllm/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own ChatOpsLLM?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.