Nyckel ML MCP Server for CrewAI 10 tools — connect in under 2 minutes
Connect your CrewAI agents to Nyckel ML through Vinkius, pass the Edge URL in the `mcps` parameter and every Nyckel ML tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Nyckel ML Specialist",
goal="Help users interact with Nyckel ML effectively",
backstory=(
"You are an expert at leveraging Nyckel ML 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 Nyckel ML "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 10 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 Nyckel ML MCP Server
Connect your Nyckel machine learning account to your AI agent and leverage powerful automated classification and semantic search through natural conversation.
When paired with CrewAI, Nyckel ML becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Nyckel ML 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
- Automated Classification — Send text or image URLs to your trained ML functions to get instant predictions and confidence scores.
- Semantic Search — Query your search function galleries to find semantically similar samples based on input data.
- Function Management — List all ML functions in your account and retrieve detailed configuration and metadata.
- Training Oversight — Access the data samples used to train your functions and monitor assigned labels.
- Sample Annotation — Upload new training samples and manually assign or update classification labels.
- Label Discovery — Retrieve the set of all available labels and categories defined for your ML models.
- Account Insights — Access profile and workspace metadata for your authenticated Nyckel account.
The Nyckel ML MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Nyckel ML to CrewAI via MCP
Follow these steps to integrate the Nyckel ML MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py. CrewAI auto-discovers 10 tools from Nyckel ML
Why Use CrewAI with the Nyckel ML MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Nyckel ML 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
Nyckel ML + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Nyckel ML MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Nyckel ML 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 Nyckel ML, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Nyckel ML 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 Nyckel ML against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Nyckel ML MCP Tools for CrewAI (10)
These 10 tools become available when you connect Nyckel ML to CrewAI via MCP:
annotate_ml_sample
Assign label to a sample
create_ml_sample
Add a training sample
delete_ml_function
Delete an ML function
get_account_info
Get current account info
get_ml_function
Get specific function info
invoke_ml_function
Classify data using a function
list_ml_functions
) in your account. List all ML functions
list_ml_labels
List available labels
list_ml_samples
List training samples
semantic_search
Perform semantic search
Example Prompts for Nyckel ML in CrewAI
Ready-to-use prompts you can give your CrewAI agent to start working with Nyckel ML immediately.
"Classify this text: 'The delivery was very late and the food was cold' using function ID 'func_123'."
"Search my product gallery for an image similar to 'https://example.com/shoe.jpg' using function 'func_search_99'."
"List all the machine learning functions in my Nyckel account."
Troubleshooting Nyckel ML MCP Server with CrewAI
Common issues when connecting Nyckel ML to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Nyckel ML + CrewAI FAQ
Common questions about integrating Nyckel ML 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.Connect Nyckel ML with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Nyckel ML to CrewAI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.