Model Context Protocolサーバーであり、VMware vCenter / ESXiのVMライフサイクル管理ツールをClaude Codeやその他のMCPクライアントに公開します。pyVmomiをベースに構築されています。
vCenterデータセンター（ホストごとにグループ化）またはスタンドアロンESXiホスト上のVMをリスト表示
VMの作成（ネットワークブート優先、シンまたはシックプロビジョニング、ESXiターゲット向けのネストされた仮想化オプション）
VMの電源オンおよびオフ
VMの削除（実行中の場合は先に電源をオフにし、その後ディスクから破棄）
検索には表示名またはmoref ID（例: vm-42）を使用できます。morefパスを使用するとインベントリスキャンをスキップできるため、大規模な環境では高速に動作します。
Related MCP server: VMWare MCP
Python 3.10以降
ネットワーク経由でアクセス可能なvCenter ServerまたはスタンドアロンESXiホスト
実行したい操作に必要な権限を持つvSphereアカウント（list_vmsには読み取り専用で十分ですが、作成や削除には対応するVMおよびリソースプールの権限が必要です）
プロジェクトローカルのvirtualenvにインストールします。venvを使用することで、vcenter-mcpとその依存関係（特にpyVmomi）をシステムPythonから分離できます。
このリポジトリをクローンした場所から実行します：
python3 -m venv .venv
.venv/bin/pip install --upgrade pip
.venv/bin/pip install -e .開発用（pytestもインストールされます）：
.venv/bin/pip install -e ".[dev]"このREADME全体を通して、コマンドは
.venv/bin/...を使用しています。シェルごとに一度source .venv/bin/activateを実行すれば、プレフィックスを省略しても同じ結果が得られます。
venvのPythonを使用して対話型セットアップを実行します：
.venv/bin/python -m vcenter_mcp setup以下の入力を求められます：
ターゲット名（例: lab-vcenter） — 後でこのターゲットを参照するために使用します
vCenter / ESXiのホスト名またはIPアドレス
ユーザー名とパスワード
ターゲットタイプ: vcenter または esxi
（vCenterのみ）データセンター名とクラスター名
データストア名
1つ以上のネットワークプロファイル（名前と1つ以上のポートグループ名の組み合わせ）
セットアップにより、~/.config/vcenter-mcp/config.json（モード 0600）に設定が書き込まれます。ターゲットを追加したり既存の設定を更新したりする場合は、いつでも再実行してください。
{
"default_target": "lab-vcenter",
"targets": {
"lab-vcenter": {
"host": "vcenter.lab.example.com",
"user": "admin@vsphere.local",
"password": "...",
"type": "vcenter",
"datacenter": "Lab DC",
"cluster": "Lab Cluster",
"datastore": "datastore1",
"networks": {
"standard": ["VM Network"],
"secure-boot": ["pg-secure-1", "pg-secure-2"]
},
"default_network": "standard"
}
},
"templates": {
"esxi": { "cpu": 4, "ram_mb": 16384, "disk_gb": 100, "disk_provisioning": "thin", "guest_id": "vmkernel7Guest", "vhv": true },
"ubuntu": { "cpu": 2, "ram_mb": 4096, "disk_gb": 40, "disk_provisioning": "thin", "guest_id": "ubuntu64Guest", "vhv": false },
"rhel": { "cpu": 2, "ram_mb": 4096, "disk_gb": 40, "disk_provisioning": "thin", "guest_id": "rhel9_64Guest", "vhv": false }
}
}ネットワークプロファイルはポートグループのリストです。最初の項目がブートNICになります。独自のVMタイプを追加するには templates にエントリを追加してください。create_vm に渡される vm_type 文字列がこの辞書と照合されます。
venvのPythonの絶対パスを使用してMCPサーバーを登録します。Claude Codeはアクティブ化されたvenvを継承しない新しいシェルでサーバーを起動するため、絶対パスが必要です。ここで単なる python を指定すると vcenter_mcp のインポートに失敗します。
VCENTER_MCP_DIR="$(pwd)" # run this from the repo root, after install
claude mcp add --scope user vcenter -- "$VCENTER_MCP_DIR/.venv/bin/python" -m vcenter_mcpまたは、使用したい絶対パスを直接指定します：
claude mcp add --scope user vcenter -- /absolute/path/to/vcenter-mcp/.venv/bin/python -m vcenter_mcp読み取りツール（list_vms）はプロンプトなしで許可しても安全です。~/.claude/settings.json の permissions.allow に追加してください：
{
"permissions": {
"allow": [
"mcp__vcenter__list_vms"
]
}
}破壊的なツール（create_vm、power_on_vm、power_off_vm、delete_vm）はデフォルトの許可リストには含まれていません。Claudeは呼び出しごとに確認を求めます。
ツール | 機能 |
| ターゲット上のVMをリスト表示します。vCenterターゲットはデータセンター内のホストごとにグループ化され、ESXiターゲットはホスト上のすべてをリスト表示します。 |
| ネットワークブートを優先するVMを作成します。 |
| 表示名またはmoref IDでVMの電源をオンにします。 |
| 表示名またはmoref IDでVMの電源を強制的にオフにします。 |
| VMを完全に削除します（実行中の場合は先に電源をオフにし、その後ディスクから破棄します）。 |
vcenter-mcp は検証なしのSSLコンテキストで接続します。これは、ラボ環境のvCenterでは自己署名証明書が非常に一般的であるため、govc やほとんどのpyVmomiサンプルコードでもデフォルトとなっている動作です。ターゲットが適切に署名された証明書を使用しており、厳密な検証が必要な場合は、src/vcenter_mcp/client.py 内の _ssl_context() を変更してください。
python3 -m venv .venv
.venv/bin/pip install -e ".[dev]"
.venv/bin/pytestテストはCI環境のPython 3.10、3.11、3.12で実行されます（.github/workflows/test.yml を参照）。
Create a VM that network boots first. vm_type: esxi, ubuntu, rhel (or any type defined in config templates). disk_provisioning: thin (default) or thick. network_profile: named profile from target config (e.g. standard, secure-boot).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| vm_type | Yes | ||
| target | No | ||
| network_profile | No | ||
| cpu | No | ||
| ram_mb | No | ||
| disk_gb | No | ||
| disk_provisioning | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden but only mentions 'network boots first' as a behavioral trait. It does not disclose whether the operation is idempotent, requires authentication, or what happens on conflict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, using four short lines with no unnecessary words. Each sentence adds value and is front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters and no output schema details, the description is incomplete: it omits required fields, resource constraints, and 5 parameters entirely. An output schema exists but does not compensate for missing parameter explanations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description only explains three parameters (vm_type, disk_provisioning, network_profile) out of eight. Critical parameters like name, cpu, ram_mb, and disk_gb are left undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Create' and the resource 'VM', and adds specificity with 'network boots first'. Sibling tools are management operations, so there is no confusion with alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives examples for vm_type and disk_provisioning defaults, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Permanently delete a VM (power off if running, then destroy from disk). Accepts display name or moref ID (e.g. 'vm-42').
| Name | Required | Description | Default |
|---|---|---|---|
| name_or_id | Yes | ||
| target | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description shoulders full transparency. It discloses the irreversible destructive action, the pre-step (power off), and the input format. Missing details like permission requirements or error behavior, but core behavioral traits are present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no extraneous information. Action and input format are front-loaded, making it efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the action and key parameter but lacks explanation for the optional 'target' parameter and does not mention output schema or return behavior, leaving gaps for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain all parameters. It clarifies that name_or_id accepts a display name or moref ID, but completely omits the 'target' parameter, leaving users without guidance on its purpose or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Permanently delete a VM' and details the process ('power off if running, then destroy from disk'), clearly differentiating it from sibling tools like list_vms or power_on_vm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to identify the VM (name or moref ID) but does not provide explicit guidance on when to use this tool versus alternatives, such as powering off or creating a snapshot.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List VMs on a target.
Standalone ESXi: lists all VMs on the host.
vCenter: groups VMs by host within the specified datacenter (defaults to the target's configured datacenter).
| Name | Required | Description | Default |
|---|---|---|---|
| target | No | ||
| datacenter | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses significant behavioral differences between standalone ESXi and vCenter, including optional datacenter grouping. Without annotations, it carries the full burden and does so well. It implies read-only operation (list) but does not explicitly state lack of side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two bullet points, front-loading the main action. Every sentence provides value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's core behavior and parameter roles. With an output schema present (context signal), return values need not be described. It is fairly complete for a list tool, though explicit mention of read-only nature would strengthen it further.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It explains the 'datacenter' parameter defaults to the target's configured datacenter but lacks detail on the 'target' parameter (e.g., format, valid values). Some meaning added, but insufficient given the gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists VMs on a target, with specific behavior for standalone ESXi vs vCenter. It uniquely identifies the resource (VMs) and action (list), distinguishing it from sibling tools like create_vm, delete_vm, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (listing VMs on a target) and mentions key parameters (target, datacenter). However, it does not explicitly state when not to use or suggest alternative tools, though siblings are distinct actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Hard power off a VM by display name or moref ID (e.g. 'vm-42').
| Name | Required | Description | Default |
|---|---|---|---|
| name_or_id | Yes | ||
| target | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose more behavioral details. It states 'hard power off' implying forceful shutdown but does not mention risks (data loss), prerequisites, or behavior if VM is already off or not found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, but lacks structure such as separate sections for usage or parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with an output schema, the description is adequate for the core action, but fails to explain the optional parameter and lacks behavioral context, leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It explains name_or_id (display name or moref ID) but completely ignores the 'target' parameter, leaving its purpose unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (hard power off) and the resource (VM), and specifies the identification methods (display name or moref ID), distinguishing it from siblings like power_on_vm or delete_vm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to hard power off a VM) but provides no explicit guidance on when not to use, such as preferring a soft shutdown or prerequisites like the VM being powered on.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Power on a VM by display name or moref ID (e.g. 'vm-42').
| Name | Required | Description | Default |
|---|---|---|---|
| name_or_id | Yes | ||
| target | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states the action without disclosing side effects (e.g., idempotency), required permissions, or error conditions. With no annotations, the agent lacks critical behavioral context for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no wasted words. Every piece of information earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and an output schema, the description covers the primary parameter but misses behavioral details (e.g., what happens if VM is already on) and the purpose of the 'target' parameter. Adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains that name_or_id accepts a display name or moref ID, adding value beyond the schema structure. However, the optional 'target' parameter is not explained, and schema coverage is 0%, so the description only partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Power on a VM') and the resource identifiers ('by display name or moref ID'), which distinguishes it from siblings like power_off_vm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies how to identify the VM (name or moref ID) with an example, but does not provide guidance on when to choose one identifier over the other or mention when not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0create_vmdelete_vmlist_vmspower_off_vmpower_on_vmScored across 5 tools
Each tool has a clearly distinct purpose: create, delete, list, power on, power off. No overlap in functionality.
All tools follow a consistent verb_noun pattern in snake_case (create_vm, delete_vm, list_vms, power_off_vm, power_on_vm). Minor plural variation for list_vms is acceptable.
5 tools cover the essential VM lifecycle operations without being excessive or insufficient for a vCenter MCP server.
Missing common operations like get single VM details, update VM configuration, clone, or snapshot management. Basic CRUD and power actions are present but gaps exist for full lifecycle management.
Provides capabilities that let LLM agents perform a range of infrastructure management tasks.
Interact with the Stitch API using natural language commands.
Manage Rackspace Spot Kubernetes Cloudspaces, node pools, and VMs from your AI assistant.
Interact with your Google Cloud Firestore resources using natural language commands.
