relevance-ai

Name: relevance-ai
Availability: InStock
Author: Relevance AI

Manage AI agents, tools, and workforces via the Relevance MCP.

1|Updated Mar 12, 2026

Search Tags:#automation #MCP #agents #knowledge #tools #workflows

Ready to run

npx skills add https://github.com/RelevanceAI/agent-skills --skill relevance-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: relevance-ai
Source: https://github.com/RelevanceAI/agent-skills/tree/main
Command: npx skills add https://github.com/RelevanceAI/agent-skills --skill relevance-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Relevance AI teams often struggle to orchestrate AI agents, attach tools, and coordinate multi-agent pipelines across MCP-connected projects. This skill provides a unified interface to create, configure, and manage agents, tools, workforces, and knowledge tables via the MCP API.

Core Features & Use Cases

Create, configure, and attach tools to agents for automated workflows
Build deterministic workforces and multi-agent pipelines with configurable handovers
Manage knowledge tables to persist context and memory across conversations
Verify MCP setup, list available tools, and orchestrate end-to-end agent workflows

Quick Start

Create an agent in MCP, attach a tool, and start a simple workflow to validate end-to-end MCP automation.

Frequently Asked Questions about relevance-ai

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

FAQPage Schema

How do I manage AI agents and attach tools via MCP?▼

To manage AI agents and attach tools via MCP, you use the Relevance MCP interface to upsert agents and configure tool attachments, enabling automated workflows across connected projects.

What is a multi-agent workforce and how does it coordinate pipelines?▼

A multi-agent workforce is a deterministic pipeline created via MCP that orchestrates multiple AI agents with configurable handovers to execute end-to-end automated workflows.

How do I persist context and memory across AI agent conversations?▼

You persist context and memory across AI agent conversations by creating and managing knowledge tables via the Relevance MCP, which stores shared data for multi-agent workflows.

Do I need a connected Relevance MCP server to orchestrate agent workflows?▼

Yes, you need a connected Relevance MCP server and an MCP-enabled tool configuration like agents/openai.yaml to verify setup and orchestrate end-to-end agent workflows.

What's the best way to build deterministic multi-agent pipelines with configurable handovers?▼

The best way to build deterministic multi-agent pipelines with configurable handovers is by using the relevance_create_workforce MCP tool to orchestrate coordinated agent workflows.