Azure MCP Server
适用于 Claude Desktop 的 Azure MCP(模型上下文协议)
模型上下文协议 (MCP) 实现,使 Claude Desktop 能够与 Azure 服务交互。此集成允许 Claude 直接通过自然语言对话查询和管理 Azure 资源。
特征
Azure 资源管理:与 Azure 资源管理客户端接口
订阅管理:列出和管理 Azure 订阅
租户管理:列出并选择 Azure 租户
自动身份验证:利用 DefaultAzureCredential 实现灵活的身份验证方法
错误处理:强大的错误处理功能,可重试瞬时故障
清洁响应格式:与 Claude Desktop 兼容的正确格式的响应
Related MCP server: Cloud PC Management MCP Server
先决条件
Node.js(v18 或更高版本)
Claude 桌面应用程序
具有适当权限的 Azure 帐户
Azure CLI(可选,用于基于 CLI 的身份验证)
安装
手动安装
克隆存储库:
git clone https://github.com/Streen9/azure-mcp.git
cd azure-mcp安装依赖项:
npm install配置Claude桌面:
打开
claude_desktop_config.json添加以下 MCP 配置:
{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-sequential-thinking"
]
},
"azure": {
"command": "tsx",
"args": [
"C:/Users/[YourUsername]/path/to/azure-mcp/src/launcher.ts"
]
}
}
}验证
服务器通过DefaultAzureCredential支持多种身份验证方法:
环境变量
托管标识
Azure CLI
Visual Studio 代码
交互式浏览器
服务器将自动按顺序尝试这些方法,直到成功为止。
用法
如果 Claude Desktop 正在运行,请关闭它(检查任务管理器)
启动 Claude Desktop
在聊天中,您现在可以询问与 Azure 相关的问题,例如:
“您能获得所有可用的 Azure 帐户和订阅吗?”
“列出我的订阅中的所有资源组”
“显示特定资源组中的所有虚拟机”
对话示例
You: Can you get all the available Azure accounts and subscriptions?
Claude: I'll help you list all available Azure tenants and subscriptions.
[Claude will then use the Azure MCP to fetch and display the information]发展
项目结构
azure-mcp/
├── src/
│ ├── launcher.ts # Server entry point
│ ├── AzureServer.ts # Main MCP server implementation
│ └── LoggerService.ts # Logging utility
├── package.json
└── README.md关键组件
AzureMCPServer :实现 MCP 协议的主服务器类
HandleCallTool :处理传入的工具请求
ExecuteWithRetry :实现弹性操作的重试逻辑
故障排除
身份验证问题:
确保您已通过 Azure CLI (
az login) 登录如果使用服务主体,请检查环境变量
验证 Azure 帐户是否具有必要的权限
连接问题:
验证 Claude Desktop 配置
检查配置文件中的路径是否符合您的安装
确保没有其他实例正在运行
常见错误:
NO_TENANT:使用“select-tenant”工具选择租户NO_CLIENTS:确保正确的初始化和身份验证CODE_EXECUTION_FAILED:检查 Azure 权限和连接
贡献
欢迎贡献代码!欢迎提交 Pull 请求。
贡献者
@calclavia——与 smithery.ai 集成
致谢
Claude Desktop 团队负责 MCP 实施
Azure SDK 团队提供全面的 SDK
用于实现 AI 服务集成的模型上下文协议
安全说明
此实现遵循 Azure 安全最佳实践:
没有硬编码凭证
安全凭证链实施
正确的错误处理和清理
对于安全问题或漏洞,请创建问题。
Available Tools
9 toolscreate-resource-groupC
Create a new resource group
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Resource group name | |
| location | Yes | Azure region | |
| tags | No | Resource tags (optional) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Create a new resource group' implies a write/mutation operation, but it doesn't address permissions required, whether this is idempotent, what happens on conflicts, rate limits, or what the response contains. This leaves significant gaps 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?
The description is a single, clear sentence with zero wasted words. It's appropriately sized for a simple creation operation and front-loads the essential information.
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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation, error conditions, or behavioral aspects. Given the complexity (creating Azure resources) and lack of structured data, more context is needed.
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 100%, so the schema already documents all parameters (name, location, tags) with their types and descriptions. The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high schema coverage.
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 ('Create') and resource ('resource group'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its siblings like 'list-resource-groups' or 'get-resource-details' beyond the obvious creation vs. listing distinction.
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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, dependencies, or scenarios where this creation operation is appropriate versus other tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-resource-detailsC
Get detailed information about a specific resource
| Name | Required | Description | Default |
|---|---|---|---|
| resourceId | Yes | Azure Resource ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), but doesn't cover critical aspects like authentication requirements, rate limits, error conditions, or what 'detailed information' entails. This is inadequate for a tool with zero annotation coverage.
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, efficient sentence with zero wasted words. It's appropriately sized for a simple lookup tool and front-loads the core purpose immediately.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'detailed information' includes, potential response formats, or behavioral constraints. For a tool with zero structured metadata, this leaves significant 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 100%, so the schema already documents the 'resourceId' parameter as an Azure Resource ID. The description adds no additional parameter semantics beyond implying it fetches details for 'a specific resource', which aligns with the schema but doesn't provide extra value.
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 ('Get') and resource ('detailed information about a specific resource'), making the purpose understandable. However, it doesn't differentiate this tool from potential sibling read operations like 'get-role-definitions' or 'get-user-permissions' beyond the generic 'resource' reference.
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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a resource ID), exclusions, or comparisons to sibling tools like 'list-resource-groups' for broader queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-role-definitionsC
List available role definitions
| Name | Required | Description | Default |
|---|---|---|---|
| scope | No | Scope for role definitions. Leave empty for subscription level. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying it's read-only, but doesn't specify if it requires authentication, rate limits, pagination behavior, or what the output format looks like. This leaves significant gaps for a tool that interacts with role definitions.
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, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded and appropriately sized for a simple list operation, making it easy to parse quickly.
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 the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like authentication needs, error handling, or output structure, which are crucial for a tool that lists role definitions in a system like Azure. The simplicity of the tool (one optional parameter) doesn't excuse these omissions.
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 input schema has 100% description coverage, with the 'scope' parameter documented as 'Scope for role definitions. Leave empty for subscription level.' The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating value.
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 ('List') and resource ('available role definitions'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'list-role-assignments' or 'get-user-permissions', but the focus on definitions rather than assignments or user-specific permissions is implied through the wording.
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 no guidance on when to use this tool versus alternatives like 'list-role-assignments' or 'get-user-permissions'. It lacks context about prerequisites, such as needing authentication or specific permissions, and doesn't mention any exclusions or scenarios where other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-user-permissionsC
Get detailed user permissions by combining role assignments and role definitions
| Name | Required | Description | Default |
|---|---|---|---|
| scope | No | Scope to check permissions for. Leave empty for subscription level. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the data sources (role assignments and definitions) but lacks behavioral details such as required permissions, rate limits, error handling, or output format. For a tool that likely involves sensitive permissions data, this is a significant gap in transparency.
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, efficient sentence that conveys the core purpose without unnecessary words. It is front-loaded with the main action. However, it could be slightly more structured by explicitly mentioning the output or usage context to improve clarity.
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 the complexity of permissions data and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., a list of permissions, aggregated view), how permissions are combined, or any behavioral traits. For a tool with no structured output documentation, this leaves significant 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 100%, so the schema already documents the single parameter 'scope' with its description. The description adds no additional meaning about parameters beyond what the schema provides, such as examples of scope values or how scope affects the permission calculation. Baseline 3 is appropriate when schema does the heavy lifting.
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 ('Get') and resource ('detailed user permissions'), and explains the mechanism ('by combining role assignments and role definitions'). It distinguishes from siblings like 'get-role-definitions' or 'list-role-assignments' by focusing on the combined result. However, it doesn't explicitly differentiate from all siblings (e.g., 'get-resource-details' might overlap in some contexts).
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 no guidance on when to use this tool versus alternatives like 'list-role-assignments' or 'get-role-definitions'. It mentions the combination of data sources but doesn't specify scenarios where this combined view is preferable over fetching the components separately. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-resource-groupsB
List all resource groups in the selected subscription
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states what the tool does, not behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what format the output takes. This is inadequate for a tool with zero annotation coverage.
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, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple list operation with no 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 list tool with no parameters and no output schema, the description covers the basic action but lacks context about authentication, subscription selection, or output format. It's minimally viable but has clear gaps given the lack of annotations.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline high score since it doesn't need to compensate for gaps.
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 ('List all') and resource ('resource groups in the selected subscription'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get-resource-details' or 'list-role-assignments', which prevents a perfect score.
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 no guidance on when to use this tool versus alternatives like 'get-resource-details' or 'list-tenants'. It mentions 'selected subscription' but doesn't explain how that selection occurs or prerequisites, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-role-assignmentsC
List role assignments for the subscription or resource group
| Name | Required | Description | Default |
|---|---|---|---|
| scope | No | Scope for role assignments (subscription, resource group, or resource ID). Leave empty for subscription level. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose critical traits like authentication requirements, rate limits, pagination, or what happens if scope is invalid. For a tool with no annotations, this leaves significant behavioral gaps.
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, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple list tool. Every word earns its place, making it highly concise and well-structured.
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 no annotations and no output schema, the description is incomplete. It doesn't explain return values, error conditions, or behavioral nuances. For a tool that likely returns a list of assignments with potential complexity, more context is needed to be fully helpful to 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 100%, with the parameter 'scope' fully documented in the schema. The description adds minimal value beyond the schema by mentioning 'subscription or resource group' context, but doesn't provide additional semantics like examples or edge cases. Baseline 3 is appropriate given high schema coverage.
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 ('List') and resource ('role assignments') with scope context ('for the subscription or resource group'). It distinguishes from siblings like 'get-role-definitions' (definitions vs assignments) and 'get-user-permissions' (permissions vs assignments). However, it doesn't explicitly differentiate from all siblings, keeping it at 4 rather than 5.
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 no guidance on when to use this tool versus alternatives. It mentions scope but doesn't specify when to use 'list-role-assignments' over 'get-user-permissions' or other sibling tools. There are no explicit when/when-not instructions or named alternatives, resulting in minimal guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-tenantsB
List all available Azure tenants
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'lists all available Azure tenants,' implying a read-only operation, but doesn't specify whether it requires authentication, returns paginated results, or has any rate limits. This leaves gaps in understanding the tool's behavior beyond the basic action.
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, clear sentence with no wasted words. It's front-loaded with the core action ('List all available Azure tenants'), making it easy to parse quickly. Every word contributes directly to the 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 the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but has gaps. It covers the basic purpose but lacks context on usage, authentication needs, or output format, which could be important for an AI agent to use it correctly in a broader Azure management scenario.
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 tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The description appropriately doesn't mention parameters, which is correct for a parameterless tool, earning a baseline score of 4 for not adding unnecessary information.
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 ('List') and resource ('Azure tenants'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'select-tenant' or 'list-resource-groups', which would require mentioning this specifically lists tenants rather than resources or role assignments.
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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), when it's appropriate (e.g., for tenant selection), or contrast with siblings like 'select-tenant' (which might choose a tenant) or 'list-resource-groups' (which lists resources within a tenant).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run-azure-codeC
Run Azure code
| Name | Required | Description | Default |
|---|---|---|---|
| reasoning | Yes | The reasoning behind the code | |
| code | Yes | Your job is to answer questions about Azure environment by writing Javascript code using Azure SDK. The code must adhere to a few rules: - Use the provided client instances: 'resourceClient' for ResourceManagementClient, 'subscriptionClient' for SubscriptionClient, and 'authorizationClient' for AuthorizationManagementClient - DO NOT create new client instances or import Azure SDK packages - Use async/await and promises - Think step-by-step before writing the code - Avoid hardcoded values like Resource IDs - Handle errors gracefully - Handle pagination correctly using for-await-of loops - Data returned must be JSON containing only the minimal amount of data needed - Code MUST "return" a value: string, number, boolean or JSON object | |
| tenantId | No | Azure Tenant ID | |
| subscriptionId | No | Azure Subscription ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Run Azure code' implies execution but doesn't disclose critical traits: whether it's read-only or mutative, authentication needs, rate limits, error handling, or output format. The input schema hints at some behaviors (e.g., code rules), but the description itself adds minimal value beyond the name.
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 extremely concise with just two words, making it front-loaded and waste-free. However, this conciseness comes at the cost of under-specification, but per the dimension's focus on size and structure, it earns full marks for brevity.
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 the complexity (code execution tool with 4 parameters, no annotations, and no output schema), the description is incomplete. It doesn't explain the tool's behavior, output, or integration context, leaving significant gaps. The input schema provides some context, but the description fails to compensate for the lack of annotations and output schema.
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 100%, so the schema fully documents all four parameters. The description adds no additional meaning about parameters beyond what's in the schema. According to the rules, with high schema coverage, the baseline score is 3 when no param info is in the description, which applies here.
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 'Run Azure code' is essentially a tautology that restates the tool name 'run-azure-code'. It doesn't specify what kind of Azure code (e.g., SDK operations, queries, management tasks) or what resources it acts upon. While it distinguishes from siblings by focusing on code execution rather than specific resource operations, it remains too vague about the actual purpose.
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?
No explicit guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context (e.g., vs. direct SDK calls or other tools), or exclusions. Without this, users must infer usage from the input schema, which is insufficient for clear decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
select-tenantC
Select Azure tenant and subscription
| Name | Required | Description | Default |
|---|---|---|---|
| tenantId | Yes | Azure Tenant ID to select | |
| subscriptionId | Yes | Azure Subscription ID to select |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Select') but doesn't explain what this means operationally—e.g., whether it sets a context for subsequent calls, requires specific permissions, has side effects like caching, or returns any confirmation. This is inadequate for a tool that likely influences session state.
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, efficient sentence with zero wasted words. It's front-loaded with the core action and resources, making it immediately understandable. This is an excellent example of conciseness.
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 the lack of annotations and output schema, the description is incomplete for a tool that likely manages session context. It doesn't explain the behavioral impact of 'selecting' (e.g., persistence, scope for other tools), return values, or error conditions. For a state-changing operation in a cloud environment, this leaves critical 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 input schema has 100% description coverage, clearly documenting both parameters (tenantId and subscriptionId) with their purposes. The description adds no additional parameter details beyond what the schema provides, so it meets the baseline score of 3 without compensating value.
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 ('Select') and the target resources ('Azure tenant and subscription'), which is specific and unambiguous. However, it doesn't differentiate this tool from sibling tools like 'list-tenants' or explain how selection differs from listing, preventing a perfect score.
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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication state), whether it's needed before other operations, or how it relates to siblings like 'list-tenants' for discovery. This leaves the agent with minimal context for appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
9 tool updates
- First observed
create-resource-group - First observed
get-resource-details - First observed
get-role-definitions - First observed
get-user-permissions - First observed
list-resource-groups - First observed
list-role-assignments - First observed
list-tenants - First observed
run-azure-code - First observed
select-tenant
TDQS
Most tools have distinct purposes targeting different Azure resources (resource groups, roles, tenants, code execution), but 'get-resource-details' is ambiguous—it could overlap with other specific getters if not clarified. The descriptions help differentiate, but this one tool creates minor confusion.
Tools mostly follow a consistent verb_noun pattern (e.g., create-resource-group, list-resource-groups, get-role-definitions), with all using kebab-case. However, 'run-azure-code' deviates slightly by including 'azure' in the noun, breaking the pure resource-focused naming seen elsewhere.
With 9 tools, this server is well-scoped for Azure management, covering core areas like resource groups, roles, tenants, and code execution. Each tool earns its place by addressing a specific aspect of Azure operations without being overly broad or sparse.
The toolset provides good coverage for Azure management, including CRUD-like operations (create/list for resource groups) and key administrative functions (roles, tenants). Minor gaps exist, such as missing update/delete for resource groups or more granular resource operations, but agents can likely work around these for common workflows.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
- platform7nOAuthtech.p7n
Connect Claude to your Platform7n workspaces — chat, links, and tasks. One-click OAuth.
Deploy, monitor, and manage your OpenClaw AI assistants via natural language.
Your AI Agent's Infrastructure Layer. Connect Claude, Copilot, Codex, or ChatGPT to 200+ managed open source services. Start databases, pipelines, and applications through natural language.
Build and manage AI-native customer support agents from Claude or any MCP client.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceIntegrates Claude Desktop with Azure AI Search, allowing users to query search indexes using keyword, vector, or hybrid search methods.55-
- AlicenseNot gradedqualityDmaintenanceEnables management of Azure Cloud PCs using the Microsoft Graph API, allowing users to list available Cloud PCs in their tenant through Claude Desktop.MIT
- AlicenseBqualityDmaintenanceEnables natural language exploration of Azure environments by generating and executing KQL queries against Azure Resource Graph. Supports multi-tenant configurations, subscription scoping, and provides direct access to Azure resource information through conversational interactions.82Apache 2.0
- AlicenseBqualityDmaintenanceEnables intelligent interaction with Azure resources through natural language by translating requests into safe, auditable Azure CLI commands with plan/review workflows and direct access to 8 Azure services including Storage, Cosmos DB, Key Vault, and more.31MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/kalivaraprasad-gonapa/azure-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server