Relevance AI MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Delete Task, Get Agent Details, Get Knowledge, and more

Name: Relevance AI
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Relevance AI as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Relevance AI MCP Server for LlamaIndex is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Relevance AI. "
            "You have 11 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Relevance AI?"
    )
    print(response)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Relevance AI MCP Server

Connect your Relevance AI account to any AI agent and take full control of your autonomous AI workforce and tool orchestration through natural conversation. Relevance AI provides a world-class platform for building and scaling multi-agent systems, and this integration allows you to trigger autonomous agents, execute custom studios (tools), and monitor long-running task histories directly from your chat interface.

LlamaIndex agents combine Relevance AI tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Agent & Workforce Orchestration — List all available autonomous agents and trigger them to perform specific goals with dynamic inputs programmatically.
Studio & Tool Intelligence — Access and monitor your custom AI 'Studios' and execute them with complex parameters directly from the AI interface.
Task Lifecycle Management — Retrieve real-time progress for background tasks and monitor final outputs to ensure your autonomous workflows are always synchronized.
Knowledge & RAG Control — List and search through your agent's knowledge base items and datasets via natural language.
Operational Monitoring — Track system activity and manage regional deployments using simple AI commands.

The Relevance AI MCP Server exposes 11 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Relevance AI tools available for LlamaIndex

When LlamaIndex connects to Relevance AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning multi-agent-systems, autonomous-agents, workflow-automation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

delete

Delete task on Relevance AI

Permanently delete a task record

get

Get agent details on Relevance AI

Get metadata for an agent

get

Get knowledge on Relevance AI

Get details for a knowledge base

get

Get task status on Relevance AI

Check status and results of a task

list

List agent tasks on Relevance AI

List recent agent tasks

list

List agents on Relevance AI

List all AI agents

list

List executions on Relevance AI

List all agent execution history

list

List knowledge items on Relevance AI

List knowledge base items

list

List tools on Relevance AI

List all studios/tools

trigger

Trigger agent on Relevance AI

Start an agent task

trigger

Trigger tool on Relevance AI

Execute a specific tool (Studio)

Connect Relevance AI to LlamaIndex via MCP

Follow these steps to wire Relevance AI into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 11 tools from Relevance AI

Why Use LlamaIndex with the Relevance AI MCP Server

LlamaIndex provides unique advantages when paired with Relevance AI through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Relevance AI tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Relevance AI tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Relevance AI, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Relevance AI tools were called, what data was returned, and how it influenced the final answer

Relevance AI + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Relevance AI MCP Server delivers measurable value.

Hybrid search: combine Relevance AI real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Relevance AI to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Relevance AI for fresh data

Analytical workflows: chain Relevance AI queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Relevance AI in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Relevance AI immediately.

"List all my available autonomous agents."

"Show me all AI agents in my workspace with their execution statistics from the last 7 days."

"Trigger the Lead Qualifier agent to analyze and score a batch of 50 new inbound leads."

Troubleshooting Relevance AI MCP Server with LlamaIndex

Common issues when connecting Relevance AI to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Relevance AI + LlamaIndex FAQ

Common questions about integrating Relevance AI MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Relevance AI tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.