Relevance AI MCP Server for CrewAIGive CrewAI instant access to 11 tools to Delete Task, Get Agent Details, Get Knowledge, and more
GDPR Free for SubscribersConnect your CrewAI agents to Relevance AI through Vinkius, pass the Edge URL in the `mcps` parameter and every Relevance AI tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
Ask AI about this MCP Server for CrewAI
The Relevance AI MCP Server for CrewAI is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminifrom crewai import Agent, Task, Crew
agent = Agent(
role="Relevance AI Specialist",
goal="Help users interact with Relevance AI effectively",
backstory=(
"You are an expert at leveraging Relevance AI tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Relevance AI "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 11 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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.
When paired with CrewAI, Relevance AI becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Relevance AI tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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 CrewAI 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 CrewAI
When CrewAI 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 task on Relevance AI
Permanently delete a task record
Get agent details on Relevance AI
Get metadata for an agent
Get knowledge on Relevance AI
Get details for a knowledge base
Get task status on Relevance AI
Check status and results of a task
List agent tasks on Relevance AI
List recent agent tasks
List agents on Relevance AI
List all AI agents
List executions on Relevance AI
List all agent execution history
List knowledge items on Relevance AI
List knowledge base items
List tools on Relevance AI
List all studios/tools
Trigger agent on Relevance AI
Start an agent task
Trigger tool on Relevance AI
Execute a specific tool (Studio)
Connect Relevance AI to CrewAI via MCP
Follow these steps to wire Relevance AI into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install CrewAI
pip install crewaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comCustomize the agent
role, goal, and backstory to fit your use caseRun the crew
python crew.py. CrewAI auto-discovers 11 tools from Relevance AIWhy Use CrewAI with the Relevance AI MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Relevance AI through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Relevance AI + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Relevance AI MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Relevance AI for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Relevance AI, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Relevance AI tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Relevance AI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Example Prompts for Relevance AI in CrewAI
Ready-to-use prompts you can give your CrewAI 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 CrewAI
Common issues when connecting Relevance AI to CrewAI through Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Relevance AI + CrewAI FAQ
Common questions about integrating Relevance AI MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Explore More MCP Servers
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