Apipie AI Automation
It allows users to programmatically interact with Apipie AI, streamlining tasks related to AI-powered API documentation and discovery.
Install
npx promptshop add apipie-ai-automationDetails
What This Skill Does
This skill automates Apipie AI operations using the Composio Apipie AI toolkit through Rube MCP. It allows users to programmatically interact with Apipie AI, streamlining tasks related to AI-powered API documentation and discovery. It's designed for developers and automation engineers.
When to Use
- Automate API documentation generation.
- Programmatically discover API endpoints.
- Integrate Apipie AI into CI/CD pipelines.
- Manage API documentation updates.
- Validate API documentation against schemas.
- Automate API testing processes.
Key Features
- Uses Rube MCP for tool access.
- Requires active Apipie AI connection.
- Discovers available tools dynamically.
- Provides a structured workflow pattern.
- Emphasizes schema compliance.
- Offers connection status checks.
Manual Installation
Automate Apipie AI operations through Composio's Apipie AI toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/apipie_ai
Prerequisites
Rube MCP must be connected (RUBE_SEARCH_TOOLS available) Active Apipie AI connection via RUBE_MANAGE_CONNECTIONS with toolkit apipie_ai Always call RUBE_SEARCH_TOOLS first to get current tool schemas
Setup
Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.
Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds Call RUBE_MANAGE_CONNECTIONS with toolkit apipie_ai If connection is not ACTIVE, follow the returned auth link to complete setup Confirm connection status shows ACTIVE before running any workflows
Tool Discovery
Always discover available tools before executing workflows:
RUBE_SEARCH_TOOLS queries: [{use_case: "Apipie AI operations", known_fields: ""}] session: {generate_id: true}
This returns available tool slugs, input schemas, recommended execution plans, and known pitfalls.
Core Workflow Pattern
Step 1: Discover Available Tools
RUBE_SEARCH_TOOLS queries: [{use_case: "your specific Apipie AI task"}] session: {id: "existing_session_id"}
Step 2: Check Connection
RUBE_MANAGE_CONNECTIONS toolkits: ["apipie_ai"] session_id: "your_session_id"
Step 3: Execute Tools
RUBE_MULTI_EXECUTE_TOOL tools: [{ tool_slug: "TOOL_SLUG_FROM_SEARCH", arguments: {/ schema-compliant args from search results /} }] memory: {} session_id: "your_session_id"
Known Pitfalls
Always search first: Tool schemas change. Never hardcode tool slugs or arguments without calling RUBE_SEARCH_TOOLS Check connection: Verify RUBE_MANAGE_CONNECTIONS shows ACTIVE status before executing tools Schema compliance: Use exact field names and types from the search results Memory parameter: Always include memory in RUBE_MULTI_EXECUTE_TOOL calls, even if empty ({}) Session reuse: Reuse session IDs within a workflow. Generate new ones for new workflows Pagination: Check responses for pagination tokens and continue fetching until complete
Quick Reference
| Operation | Approach |
|---|---|
| Find tools | RUBE_SEARCH_TOOLS with Apipie AI-specific use case |
| Connect | RUBE_MANAGE_CONNECTIONS with toolkit apipie_ai |
| Execute | RUBE_MULTI_EXECUTE_TOOL with discovered tool slugs |
| Bulk ops | RUBE_REMOTE_WORKBENCH with run_composio_tool() |
| Full schema | RUBE_GET_TOOL_SCHEMAS for tools with schemaRef |
Automate Apipie AI operations through Composio's Apipie AI toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/apipie_ai