Relevance AI MCP Server for LangChainGive LangChain 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

LangChain is the leading Python framework for composable LLM applications. Connect Relevance AI through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

Open in ChatGPT Open in Claude Open in Perplexity

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

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "relevance-ai-alternative": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Relevance AI, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Relevance AI through native MCP adapters. Connect 11 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain

When LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 11 tools from Relevance AI via MCP

Why Use LangChain with the Relevance AI MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Relevance AI MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Relevance AI queries for multi-turn workflows

Relevance AI + LangChain Use Cases

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

RAG with live data: combine Relevance AI tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Relevance AI, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Relevance AI tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Relevance AI tool call, measure latency, and optimize your agent's performance

Example Prompts for Relevance AI in LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Relevance AI + LangChain FAQ

Common questions about integrating Relevance AI MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.