Provides HTTP endpoint integration for CrewAI agents to access Obscura AI's Workflow Builder, allowing AI agents to generate visual business automation workflows through API calls.
Enables integration with Continue.dev in JetBrains IDEs to access Obscura AI's Workflow Builder, allowing coding assistants to generate visual business automation workflows.
Provides HTTP endpoint integration for LangChain frameworks to access Obscura AI's Workflow Builder, enabling LLM applications to generate visual business automation workflows through API calls.
Provides contact information for Obscura AI support via WhatsApp, enabling communication with the service provider for assistance with workflow generation and automation.
Describe any business process. Get a visual AI automation workflow you can edit, export, and share — inside Claude, Cursor, Windsurf, your terminal, or any MCP-compatible client.
Try the Builder free | Website
This MCP server connects your AI assistant or coding agent to Obscura AI's Workflow Builder. When you ask it to map out a business automation, it generates an interactive visual workflow and gives you a link to open, edit, and share it.
No API key. No signup. No cost.
You: "Map out an automation for guest check-in at my hotel"
Claude / Cursor / your agent: Here's your workflow — 6 steps covering booking confirmation through post-stay review.
Open your workflow: https://obscuraai.xyz/builder?d=eJxVjk...
The link opens a visual canvas where you can drag nodes, edit labels, and export or share the flow.
Related MCP server: task-orchestrator
Client | Type |
Claude Desktop | Desktop app |
Claude Code | CLI / terminal |
Cursor | IDE |
Windsurf | IDE |
Cline | VS Code extension |
Continue.dev | VS Code / JetBrains |
Zed | Editor |
Any MCP stdio client | CLI / custom agents |
HTTP direct | LangChain, CrewAI, custom LLMs |
Industry | Example workflows |
Hospitality | Guest comms, table reservations, supplier coordination, event planning |
Real Estate | Property pipeline, tenant management, document processing |
Agencies | Client onboarding, content pipeline, lead qualification |
Legal | Document intelligence, case intake, compliance |
Finance | KYC checks, reporting pipelines, invoice automation |
14 pre-built workflow templates with industry-aware label customization.
Add to your config file:
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"]
}
}
}Restart Claude Desktop. You'll see "obscura" in your connected tools.
claude mcp add obscura -- npx -y @obscuraai/mcp-serverAdd to your MCP settings (usually mcp.json or equivalent):
{
"mcpServers": {
"obscura": {
"command": "npx",
"args": ["-y", "@obscuraai/mcp-server"]
}
}
}npx -y @obscuraai/mcp-serverThe server speaks JSON-RPC over stdin/stdout — pipe messages directly from any agent.
POST https://obscuraai.xyz/api/mcp
Content-Type: application/jsonNo auth required. Call it from any HTTP-capable agent or LLM framework.
generate_obscura_workflowGenerates a visual workflow and returns a shareable link to the interactive canvas.
Parameter | Type | Required | Description |
| string | Yes | The business process to automate |
| string | No |
|
Try asking your agent:
"Map out an automation for lead qualification at my agency"
"Design a guest communications workflow for a Dubai hotel"
"Build a document processing pipeline for a law firm"
"Create a tenant maintenance request flow for property management"
Obscura AI builds custom AI workflows, agents, and automations for modern businesses. We deploy systems in days, not months.
Founder: Prince Adza
Website: obscuraai.xyz
Email: prince@obscuraai.xyz
WhatsApp: +447466314822
Markets served: Dubai, Monte Carlo, South Africa, Singapore, London, and expanding across North America and Europe.
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.
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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