
Big Data Cloud Automation
- 7 installs
- 71.8k repo stars
- Updated July 24, 2026
- composiohq/awesome-claude-skills
Automate BigDataCloud IP geolocation and network data lookups from Claude by running the Big Data Cloud toolkit through the Composio Rube MCP server.
About
Wraps the Big Data Cloud toolkit behind Composio's Rube MCP so Claude can run geolocation and data-lookup operations via searched tool schemas. A developer uses it to let an agent query Big Data Cloud after connecting the toolkit.
- Requires Rube MCP connected and an ACTIVE Big Data Cloud connection
- Always call RUBE_SEARCH_TOOLS first to get current tool schemas
Big Data Cloud Automation by the numbers
- 7 all-time installs (skills.sh)
- Ranked #1,587 of 2,715 Automation & Workflows skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 7 |
|---|---|
| repo stars | ★ 71.8k |
| Last updated | July 24, 2026 |
| Repository | composiohq/awesome-claude-skills ↗ |
What it does
Automate BigDataCloud IP geolocation and network data lookups from Claude by running the Big Data Cloud toolkit through the Composio Rube MCP server.
Files
Big Data Cloud Automation via Rube MCP
Automate Big Data Cloud operations through Composio's Big Data Cloud toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/big_data_cloud
Prerequisites
- Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
- Active Big Data Cloud connection via
RUBE_MANAGE_CONNECTIONSwith toolkitbig_data_cloud - Always call
RUBE_SEARCH_TOOLSfirst 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.
1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds 2. Call RUBE_MANAGE_CONNECTIONS with toolkit big_data_cloud 3. If connection is not ACTIVE, follow the returned auth link to complete setup 4. Confirm connection status shows ACTIVE before running any workflows
Tool Discovery
Always discover available tools before executing workflows:
RUBE_SEARCH_TOOLS
queries: [{use_case: "Big Data Cloud 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 Big Data Cloud task"}]
session: {id: "existing_session_id"}Step 2: Check Connection
RUBE_MANAGE_CONNECTIONS
toolkits: ["big_data_cloud"]
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_CONNECTIONSshows ACTIVE status before executing tools - Schema compliance: Use exact field names and types from the search results
- Memory parameter: Always include
memoryinRUBE_MULTI_EXECUTE_TOOLcalls, 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 Big Data Cloud-specific use case |
| Connect | RUBE_MANAGE_CONNECTIONS with toolkit big_data_cloud |
| 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 |
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