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Let AI agents directly manage VMware vSphere infrastructure and VM operations.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "VMWare-MCP-server-for-LLMs" yet — see the docs or source repo.
Connect to VMware vSphere, list the current virtual machines, and create a new VM named test-vm; then return its status and basic configuration.
A list of existing VMs, the creation result for the new VM, and the VM’s status and basic details.
Find the virtual machine named app-server, create a pre-deployment snapshot for it, and tell me whether the snapshot was created successfully.
The identified target VM, the snapshot creation result, and a status message.
List the available datastores and network resources in vSphere and summarize them for a pre-deployment check.
A list of datastore and network resources, organized into a concise deployment-readiness summary.
DevOps engineers can let an AI agent use this MCP tool to perform VM creation, status checks, and lifecycle management in vSphere, reducing manual console work.
Before application releases or system changes, teams can use an AI agent to create snapshots for target VMs as a safeguard and rollback preparation.
When teams need visibility into available vSphere resources, they can use this tool to inspect datastore and networking information for deployment checks or inventory reviews.
This is an MCP server that gives AI agents direct access to VMware vSphere infrastructure. It supports VM lifecycle management, snapshots, datastore operations, networking, and more through 55 typed tools built on govc.
The provided description says it is built on govc and exposes its capabilities through 55 typed tools. For more implementation details, see the source repository.
The known prerequisite is access to a VMware vSphere environment. The provided material does not specify installation steps, authentication, or runtime requirements; see the source repository.
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