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Add Parallel AI Integration

Integrate Parallel AI MCP services for web research into NanoClaw.

Updated Feb 14, 2026
Search Tags:#automation#agent#mcp#web research#nanoclaw#parallel ai#task api
One-click install
npx skills add https://github.com/b9b4ymiN/JellyCore --skill add-parallel-ai-integration-b9b4ymin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Add Parallel AI Integration
Source: https://github.com/b9b4ymiN/JellyCore/tree/main/nanoclaw/.claude/skills/add-parallel
Command: npx skills add https://github.com/b9b4ymiN/JellyCore --skill add-parallel-ai-integration-b9b4ymin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill integrates Parallel AI's advanced web research capabilities into NanoClaw, allowing for quick web lookups and deep, comprehensive analysis of complex topics without blocking the agent.

Core Features & Use Cases

  • Quick Search: Perform fast web lookups using the Parallel Search API. Ideal for factual questions, current events, and quick verifications.
  • Deep Research: Conduct in-depth analysis using the Parallel Task API for complex topics, comparisons, and historical overviews. Requires user permission.
  • Non-blocking Design: Utilizes the NanoClaw scheduler to poll for results, ensuring the agent remains responsive during lengthy research tasks.
  • Use Case: Ask your AI assistant "What are the latest advancements in renewable energy?" for a quick summary, or "Explain the historical impact of the printing press" for a detailed analysis.

Quick Start

Send a message to your assistant asking for the latest news about AI to test the quick search functionality.

Frequently Asked Questions about Add Parallel AI Integration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate web research into an AI agent without blocking its responsiveness?▼

To integrate web research without blocking your AI agent, configure an HTTP MCP server to handle search and task APIs. A non-blocking scheduler polls for results during deep research, keeping the agent responsive.

What is the difference between quick web search and deep task research in MCP services?▼

Quick web search via a Search API handles fast factual lookups and current events. Deep task research uses a Task API for comprehensive analysis of complex topics, requiring user permission and utilizing a scheduler to poll for results.

Can I use the Parallel AI Task API for comprehensive historical analysis?▼

Yes, you can use the Parallel AI Task API for comprehensive historical analysis. It conducts in-depth research on complex topics and comparisons using a non-blocking scheduler to manage the lengthy task execution without blocking the agent.

How do I configure an orchestrator to use HTTP MCP servers for web research?▼

Configure HTTP MCP servers in your orchestrator and update the allowed tools to enable web research. This integration allows the agent to execute quick searches and deep task research via the configured APIs.

Do I need user permission to run deep research tasks with an AI agent?▼

Yes, deep research tasks using the Task API require user permission before execution. This ensures user control over lengthy, comprehensive analysis operations while the non-blocking scheduler manages the background polling.

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