Can I provide input parameters when running a process?

Yes, the `run_process` tool accepts an optional JSON object for parameters, allowing you to pass dynamic data to your serverless functions.

How do I check if a process execution failed?

Use the `list_executions` query. It will return a history of recent runs along with their final status (e.g., success, error, pending).

Is it possible to see the code of my processes via AI?

Yes, you can use the `get_process_details` tool to retrieve the complete metadata and code configuration for any specific process ID.

INSTANT PLUG AND PLAY

YepCode MCP Server for CrewAIGive CrewAI instant access to 6 tools to Get Process Details, List Executions, List Processes, and more

Name: YepCode
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 6 Tools Framework

Connect your CrewAI agents to YepCode through Vinkius, pass the Edge URL in the `mcps` parameter and every YepCode tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The YepCode app connector for CrewAI is a standout in the Ship It category — giving your AI agent 6 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="YepCode Specialist",
    goal="Help users interact with YepCode effectively",
    backstory=(
        "You are an expert at leveraging YepCode 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 YepCode "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

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

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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 YepCode MCP Server

Connect your YepCode account to any AI agent and simplify how you automate complex data integrations and serverless workflows through natural conversation.

When paired with CrewAI, YepCode becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call YepCode 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

Process Control — List and trigger serverless processes with custom parameters directly from your agent.
Execution Monitoring — Track the history and status of your workflow runs to ensure reliability.
Secret Management — List and verify account secrets used in your automations without exposing values.
Team Coordination — Query available teams and workspaces to understand your development environment.

The YepCode MCP Server exposes 6 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.

All 6 YepCode tools available for CrewAI

When CrewAI connects to YepCode through Vinkius, your AI agent gets direct access to every tool listed below — spanning serverless, workflow-automation, data-integration, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

get_process_details

Get details for a specific process

list_executions

List recent process executions

list_processes

List YepCode processes

list_secrets

List account secrets

list_teams

List available teams

run_process

Trigger a process execution

Connect YepCode to CrewAI via MCP

Follow these steps to wire YepCode into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 6 tools from YepCode

Why Use CrewAI with the YepCode MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with YepCode 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

YepCode + CrewAI Use Cases

Practical scenarios where CrewAI combined with the YepCode MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries YepCode 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 YepCode, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain YepCode 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 YepCode against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for YepCode in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with YepCode immediately.

"Show me all available processes in my YepCode account."

"Run the 'Data Export' process with the parameter { "format": "csv" }."

"Check the status of my recent process executions."

Troubleshooting YepCode MCP Server with CrewAI

Common issues when connecting YepCode to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

YepCode + CrewAI FAQ

Common questions about integrating YepCode MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard 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?

Yes. Each agent has its own 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?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using 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)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.