Skill UI

Automate Gleap support and analytics operations with Composio’s Gleap toolkit via Rube MCP, always querying `RUBE_SEARCH_TOOLS`, verifying `RUBE_MANAGE_CONNECTIONS`, and executing schema-safe workflows through `RUBE_MULTI_EXECUTE_TOOL`.

Automate Google Classroom workflows through Composio’s toolkit by querying Rube MCP, ensuring you always call RUBE_SEARCH_TOOLS first to fetch current schemas, verify connections, and execute schema-compliant tool calls with consistent session reuse.

Automates Google Search Console workflows via Rube MCP so you can list verified sites, query search analytics, inspect URLs, and manage sitemaps while keeping an eye on performance metrics in one integrated toolkit.

Automate Helloleads operations by discovering and invoking Composio toolkit tools through Rube MCP, always querying `RUBE_SEARCH_TOOLS` for current schemas, ensuring active connections, and executing workflows via `RUBE_MULTI_EXECUTE_TOOL` with proper memory/session handling.

Automate Jira tasks through Composio’s Rube MCP connector, covering issue search, creation, edits, agile boards, comments, projects, and user roles while always querying latest tool schemas.

This comprehensive guide assists developers in planning and executing upgrades for systems utilizing the Juicebox API. It covers critical steps such as API version detection, migrating complex data schemas (e.g., search results), updating query syntax, and implementing robust rollback strategies. Essential for maintaining continuous operation in recruiting and market research applications when the underlying API changes.

Defines MCP server tooling with file search, query execution, resource endpoints, prompt templates, and transport configurations alongside a client setup example for streamlined project automation.

Automate Missive operations by querying Composio’s Rube MCP toolkit, ensuring you search for current schemas first, maintain active connections, and execute workflows via RUBE_MULTI_EXECUTE_TOOL with schema-compliant arguments and shared session IDs.

This skill provides deep integration with Google NotebookLM, enabling users to query uploaded documentation using Gemini. It ensures source-grounded, citation-backed answers, significantly reducing hallucinations. Features include managing the notebook library (add, list, search), handling authentication, and implementing a structured follow-up mechanism for comprehensive research.

A comprehensive workflow designed for clinical professionals to search, retrieve, and synthesize medical evidence. It allows users to query clinical literature with specialized filters (e.g., specialty, evidence level), check potential drug interactions against patient profiles, and look up the latest specialty guidelines from major health organizations (like ACC/AHA, NICE). The output provides structured citations, confidence scores, and evidence grading to support informed clinical decision-making.

This system implements Role-Based Access Control (RBAC) for OpenEvidence, an AI-powered clinical decision support platform. It strictly manages access to sensitive data, including PHI-adjacent datasets and medical literature, ensuring compliance with regulations like HIPAA. The system defines distinct roles—Admin, Clinician, Researcher, Student, and Auditor—with granular permissions for querying, data export, and institutional configuration, maintaining a secure and auditable data environment.

A comprehensive guide to implementing Perplexity's API integration at various scales. It provides three validated architectural blueprints—Direct Widget, Cached Research Layer, and Multi-Query Pipeline—allowing developers to choose the optimal structure based on required query volume, latency goals, and complexity. Learn how to scale from simple search widgets to automated, high-volume research pipelines.