Can my AI agent create tasks in specific Ayanza projects?

Yes! Your agent can list all projects to find the correct ID and then create tasks directly within that project context.

Is it possible to recover deleted tasks via the AI agent?

Currently, the MCP server supports the deletion of tasks, but recovery must be handled directly within the Ayanza web interface.

Can the agent access private wiki pages?

The AI agent can only access wiki pages that are visible to the user associated with the provided API token.

Ayanza MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Ayanza
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Ayanza Specialist",
    goal="Help users interact with Ayanza effectively",
    backstory=(
        "You are an expert at leveraging Ayanza 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 Ayanza "
        "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)

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 Ayanza MCP Server

Orchestrate your team's rhythm with Ayanza, the AI-first project management platform designed for modern velocity. By connecting Ayanza to your AI agent, you transform project oversight from a manual chore into a natural conversation. Your agent gains the power to navigate complex task workflows, access team wikis, and manage project milestones without you ever opening a dashboard. It’s not just about tracking tasks; it’s about giving your agent the context it needs to act as a digital coordinator within your workspace.

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

Task Orchestration — List, create, update, and delete tasks in Ayanza using natural language through your AI agent.
Project Oversight — Get a comprehensive view of all projects or dive into specific project details to monitor progress effortlessly.
Knowledge Retrieval — Access and list wiki pages to quickly find team documentation and shared knowledge.
Workspace Management — View workspace users to understand team structure and assign tasks effectively.
Dynamic Updates — Modify task descriptions and statuses in real-time to keep your team aligned and productive.

The Ayanza 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 Ayanza to CrewAI via MCP

Follow these steps to integrate the Ayanza 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 Ayanza

Why Use CrewAI with the Ayanza MCP Server

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

Ayanza + CrewAI Use Cases

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

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

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

Ayanza MCP Tools for CrewAI (10)

These 10 tools become available when you connect Ayanza to CrewAI via MCP:

create_task

Create a new task in Ayanza

delete_task

Delete an Ayanza task

get_me

Get current authenticated user info

get_project

Get details for a specific Ayanza project

get_task

Get details for a specific Ayanza task

list_projects

List projects in Ayanza

list_tasks

List tasks in Ayanza

list_users

List users in the Ayanza workspace

list_wiki_pages

List wiki pages in Ayanza

update_task

Update an existing Ayanza task

Example Prompts for Ayanza in CrewAI

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

"List all my tasks in Ayanza."

"Create a new task called 'Prepare Q4 presentation'."

"Show my wiki pages in Ayanza."

Troubleshooting Ayanza MCP Server with CrewAI

Common issues when connecting Ayanza 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.

Ayanza + CrewAI FAQ

Common questions about integrating Ayanza 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.