Where do I get my Knoema API credentials?

Visit the **Knoema Developer Portal** (knoema.com/dev), create an application, and you will receive a Client ID and Client Secret.

How can I find a specific dataset ID?

Use the `search_datasets` tool with relevant keywords. The tool will return a list of matching datasets along with their unique IDs.

What is a mnemonic in Knoema?

A mnemonic is a short, human-readable code used to identify a specific data series within a dataset (e.g., 'NGDP' for Nominal GDP).

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

Name: Knoema
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Knoema through Vinkius, pass the Edge URL in the `mcps` parameter and every Knoema 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

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

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

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* 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 Knoema MCP Server

Connect your AI agent to Knoema, the most comprehensive source of global decision-making data.

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

Dataset Discovery — Search through millions of datasets from official sources like IMF, World Bank, and UN
Data Retrieval — Fetch precise time-series data using mnemonics for your analysis and forecasting
Metadata Auditing — Get detailed information about data sources, units, and frequencies
Granular Search — Find specific indicators (e.g., GDP, CPI, Crude Oil Price) across multiple providers
Visualization Support — Access atlas and dashboard resources for visual data context

Use Cases

Economic Analysis — gather historical and current macro indicators for market research
Business Planning — use demographic and sector data to inform strategy
Scientific Research — find environmental and social datasets for academic or professional studies

The Knoema 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 Knoema to CrewAI via MCP

Follow these steps to integrate the Knoema 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 Knoema

Why Use CrewAI with the Knoema MCP Server

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

Knoema + CrewAI Use Cases

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

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

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

Knoema MCP Tools for CrewAI (10)

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

get_data_series

Requires dataset ID and a list of mnemonics. Get specific data series

get_dataset_metadata

Critical for understanding what variables are available. Get metadata for a specific dataset

get_knoema_resource

Get a generic frontend resource

get_latest_dataset_data

Get the most recent data points for a dataset

list_data_frequencies

g., Annual, Quarterly, Monthly). List available data frequencies

list_data_topics

g., Agriculture, Economy, Demographics). List all available data topics in Knoema

list_data_units

g., Percentage, USD, Kilograms). List measurement units

list_dataset_regions

) supported by a specific dataset. List regions available in a dataset

search_data_series

More granular than dataset search. Ideal for finding specific indicators. Search for specific data series across all datasets

search_datasets

Returns dataset IDs and metadata. Use this to find the correct data source for your statistics. Search for datasets in Knoema

Example Prompts for Knoema in CrewAI

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

"Search for datasets about renewable energy in Europe"

"Get the metadata for dataset 'IMFWEOS2024Oct'"

"Search for crude oil price series"

Troubleshooting Knoema MCP Server with CrewAI

Common issues when connecting Knoema 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.

Knoema + CrewAI FAQ

Common questions about integrating Knoema 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.