描述任何业务流程。获取一个可以在 Claude、Cursor、Windsurf、终端或任何兼容 MCP 的客户端中进行编辑、导出和共享的可视化 AI 自动化工作流。
此 MCP 服务器将您的 AI 助手或编码代理连接到 Obscura AI 工作流构建器。当您要求它规划业务自动化时，它会生成一个交互式可视化工作流，并为您提供一个用于打开、编辑和共享它的链接。
无需 API 密钥。无需注册。免费使用。
您： “为我的酒店客人办理入住手续规划一个自动化流程”
Claude / Cursor / 您的代理： 这是您的工作流——涵盖从预订确认到入住后评价的 6 个步骤。
打开您的工作流： https://obscuraai.xyz/builder?d=eJxVjk...
该链接会打开一个可视化画布，您可以在其中拖动节点、编辑标签并导出或共享流程。
Related MCP server: task-orchestrator
客户端 | 类型 |
Claude Desktop | 桌面应用 |
Claude Code | CLI / 终端 |
Cursor | IDE |
Windsurf | IDE |
Cline | VS Code 扩展 |
Continue.dev | VS Code / JetBrains |
Zed | 编辑器 |
Any MCP stdio client | CLI / 自定义代理 |
HTTP direct | LangChain, CrewAI, 自定义 LLM |
行业 | 示例工作流 |
酒店业 | 客人沟通、餐桌预订、供应商协调、活动策划 |
房地产 | 房产流程、租户管理、文档处理 |
代理机构 | 客户入职、内容流程、潜在客户资格认证 |
法律 | 文档智能、案件受理、合规性 |
金融 | KYC 检查、报告流程、发票自动化 |
包含 14 个预构建的工作流模板，并支持行业感知的标签自定义。
添加到您的配置文件中：
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"obscura": {
"command": "npx",
"args": ["-y", "@obscuraai/mcp-server"]
}
}
}重启 Claude Desktop。您将在已连接的工具中看到 "obscura"。
claude mcp add obscura -- npx -y @obscuraai/mcp-server添加到您的 MCP 设置中（通常是 mcp.json 或等效文件）：
{
"mcpServers": {
"obscura": {
"command": "npx",
"args": ["-y", "@obscuraai/mcp-server"]
}
}
}npx -y @obscuraai/mcp-server该服务器通过 stdin/stdout 使用 JSON-RPC 进行通信——直接从任何代理管道传输消息。
POST https://obscuraai.xyz/api/mcp
Content-Type: application/json无需身份验证。从任何支持 HTTP 的代理或 LLM 框架调用它。
generate_obscura_workflow生成可视化工作流并返回指向交互式画布的可共享链接。
参数 | 类型 | 必填 | 描述 |
| string | 是 | 要自动化的业务流程 |
| string | 否 |
|
尝试询问您的代理：
“为我的代理机构规划一个潜在客户资格认证的自动化流程”
“为迪拜的一家酒店设计一个客人沟通工作流”
“为律师事务所构建一个文档处理流程”
“为物业管理创建一个租户维护请求流程”
Obscura AI 为现代企业构建定制的 AI 工作流、代理和自动化系统。我们可以在几天内（而非几个月）部署系统。
创始人： Prince Adza
网站： obscuraai.xyz
电子邮件： prince@obscuraai.xyz
WhatsApp： +447466314822
服务市场： 迪拜、蒙特卡洛、南非、新加坡、伦敦，并正在向北美和欧洲扩展。
MIT
Generate a visual AI automation workflow for a business process. Returns a shareable link to an interactive canvas on obscuraai.xyz where the workflow can be viewed, edited, and exported. Use when a user wants to map out an automation, workflow, or AI system for their business.
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | Describe the business process to automate. Include the industry and specific pain point if possible. | |
| industry | No | Primary industry (optional) |
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. It mentions the output ('shareable link') and that the workflow can be 'viewed, edited, and exported,' but lacks details on permissions, rate limits, error handling, or whether the generation is idempotent. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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 and front-loaded, stating the purpose and output in the first sentence. The second sentence adds usage context without redundancy. Both sentences earn their place, but minor improvements in clarity could push it to a perfect score.
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 partially compensates by explaining the output format and usage. However, it lacks details on behavioral traits like error conditions or performance, and does not fully address the complexity of a workflow generation tool. It is minimally adequate but has 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 does not explicitly discuss parameters, but the input schema has 100% description coverage, clearly documenting both parameters. The description implies parameter use through 'Describe the business process to automate' but adds no additional meaning beyond the schema. With high schema coverage, the baseline score of 3 is appropriate.
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's purpose: 'Generate a visual AI automation workflow for a business process.' It specifies the verb ('Generate') and resource ('visual AI automation workflow'), and mentions the output ('Returns a shareable link to an interactive canvas on obscuraai.xyz'). However, since there are no sibling tools, it cannot distinguish from alternatives, 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 some usage guidance: 'Use when a user wants to map out an automation, workflow, or AI system for their business.' This implies the context but does not explicitly state when not to use it or compare to alternatives. Since there are no sibling tools, the lack of alternatives is understandable, but the guidance remains basic.
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.
v1.0.4generate_obscura_workflowScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to compare it to. The tool's purpose is clearly defined and distinct by default.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'generate_obscura_workflow' follows a clear verb_noun pattern, but there are no other tools to assess consistency across a set.
A single tool is too few for the server's apparent purpose of generating and managing visual AI automation workflows, as it lacks operations for viewing, editing, or exporting workflows beyond the initial generation. This minimal scope will likely cause agent failures due to incomplete functionality.
The tool surface is severely incomplete for the domain of workflow automation; it only provides generation without any CRUD operations (e.g., no tools to list, update, delete, or retrieve existing workflows), leaving significant gaps that will hinder agent effectiveness.
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