Zenodo MCP Server for CrewAIGive CrewAI instant access to 14 tools to Create Deposition, Delete Deposition, Delete Deposition File, and more

Name: Zenodo
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Zenodo MCP Server for CrewAI is a standout in the Knowledge Management category — giving your AI agent 14 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Zenodo Specialist",
    goal="Help users interact with Zenodo effectively",
    backstory=(
        "You are an expert at leveraging Zenodo 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 Zenodo "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 14 available tools "
        "and what they can do."
    ),
)

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

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About Zenodo MCP Server

Connect your Zenodo account to any AI agent to streamline your scientific research workflows and data management through natural conversation.

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

Deposition Management — Create new unpublished depositions, update metadata, and manage your research drafts directly from the AI.
Record Discovery — Search and list public records across the entire Zenodo database to find relevant research, software, or datasets.
File Inspection — List all files attached to specific depositions to understand the contents of a research package.
Metadata Control — Precisely update titles, creators, descriptions, licenses, and access rights for your unpublished work.
Version Tracking — Retrieve specific deposition details using unique IDs to monitor the status of your submissions.

The Zenodo MCP Server exposes 14 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 14 Zenodo tools available for CrewAI

When CrewAI connects to Zenodo through Vinkius, your AI agent gets direct access to every tool listed below — spanning open-access, research-data, metadata-management, 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.

create

Create deposition on Zenodo

You can optionally provide metadata. Create a new Zenodo deposition

delete

Delete deposition on Zenodo

Note: Only unpublished depositions can be deleted. Delete an unpublished Zenodo deposition

delete

Delete deposition file on Zenodo

Delete a file from a Zenodo deposition

discard

Discard deposition on Zenodo

Discard edits on a Zenodo deposition

edit

Edit deposition on Zenodo

Edit a published Zenodo deposition

get

Get deposition on Zenodo

Retrieve a Zenodo deposition by ID

get

Get record on Zenodo

Retrieve a published Zenodo record by ID

list

List deposition files on Zenodo

List files in a Zenodo deposition

list

List depositions on Zenodo

List Zenodo depositions

list

List records on Zenodo

Search published Zenodo records

new

New version deposition on Zenodo

Create a new version of a Zenodo deposition

publish

Publish deposition on Zenodo

WARNING: Once published, a deposition cannot be deleted. Publish a Zenodo deposition

update

Update deposition on Zenodo

Update a Zenodo deposition

upload

Upload deposition file on Zenodo

Upload a text file to a Zenodo deposition

Connect Zenodo to CrewAI via MCP

Follow these steps to wire Zenodo into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind 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 14 tools from Zenodo

Why Use CrewAI with the Zenodo MCP Server

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

Zenodo + CrewAI Use Cases

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

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

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

Example Prompts for Zenodo in CrewAI

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

"Search for public Zenodo records related to 'machine learning in healthcare'."

"Create a new Zenodo deposition for a dataset titled 'Global Temperature Trends 2023'."

"List all files currently attached to my deposition with ID 987654."

Troubleshooting Zenodo MCP Server with CrewAI

Common issues when connecting Zenodo to CrewAI through 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.

Zenodo + CrewAI FAQ

Common questions about integrating Zenodo 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.