How to Use the Eden AI MCP in CrewAI

Q: How do I configure CrewAI to use Eden AI tools?

Install crewaitools. Pass your Vinkius endpoint URL directly into the mcps array when defining your agent. The framework automatically exposes the tools to that specific crew member.

Q: Can I restrict which Eden AI tools a CrewAI agent sees?

Yes. Use MCPServerHTTP from crewai.mcp and apply a toolfilter. This lets you give the finance agent access to usage stats while restricting the operations agent to workflow configurations.

Q: What happens to my Eden AI metadata when CrewAI reads it?

Tools like getedenaimetadata fetch your account credit balance. Vinkius processes this request in a stateless container. The connection closes immediately after the data transfers, ensuring your account details never linger on disk.

Deploy specialized CrewAI agents to monitor Eden AI usage, audit providers, and configure workflows autonomously.

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Connect Eden AI MCP to CrewAI

Create your Vinkius account to connect Eden AI to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Eden AI with CrewAI

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Autonomous Provider Audits

The `quick_ai_provider_audit` and `list_ai_providers` tools let a dedicated researcher agent evaluate vendor availability. This agent scans the MCP Server for active text analysis endpoints. It compiles a report on which systems are healthy. A secondary manager agent reads this report alongside `list_all_llm_models`. It decides which models the rest of the crew should use for their tasks. You get dynamic model selection without hardcoding vendor names.

Track CrewAI Costs via MCP Server

Assign a finance agent to run `get_api_usage_statistics` and `get_eden_ai_metadata`. This agent checks your Eden AI credit balance and historical API consumption. If the crew burns through credits too fast, the agent triggers an escalation protocol. Before the crew starts a massive data extraction, it calls `get_ai_feature_pricing`. The agents negotiate the cheapest path forward based on the returned cost matrices. They optimize your billing autonomously.

Map Platform Workflows

Your operations agent uses `list_ai_workflows` and `list_latest_ai_automations` to map out existing platform pipelines. It identifies the most recent changes to your automation setup. The crew adapts its behavior to match the current backend logic. When an agent needs specifics, it runs `get_workflow_configuration` to extract the exact JSON settings for a target pipeline. It also checks `list_available_ai_features` to see what subfeatures are active. The team executes tasks with complete awareness of platform constraints.

Setup guide

Set up Eden AI MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Eden AI tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Eden AI Analyst",
    goal="Access and analyze Eden AI data via MCP.",
    backstory="Expert analyst with direct Eden AI access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Eden AI transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Eden AI Analyst",
        goal="Access and analyze Eden AI data via MCP.",
        backstory="Expert analyst with direct Eden AI access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Eden AI transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Eden AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Eden AI MCP in CrewAI

Install `crewai[tools]`. Pass your Vinkius endpoint URL directly into the `mcps` array when defining your agent. The framework automatically exposes the tools to that specific crew member.

Yes. Use `MCPServerHTTP` from `crewai.mcp` and apply a `tool_filter`. This lets you give the finance agent access to usage stats while restricting the operations agent to workflow configurations.

CrewAI relies on shared memory. When one agent pulls pipeline settings using `get_workflow_configuration`, it writes the findings to the context window. Subsequent agents read that context instead of making redundant API calls.

Yes. You set up your tasks sequentially. The first agent audits providers, the second checks pricing, and the third executes the workflow based on those findings.

Tools like `get_eden_ai_metadata` fetch your account credit balance. Vinkius processes this request in a stateless container. The connection closes immediately after the data transfers, ensuring your account details never linger on disk.

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