How do I get a Determ API Key?

Log in to your Determ account, navigate to **Settings > API**, and you can retrieve your unique API Key from that section.

Can the agent show the full text of an article?

Yes, you can use the get_mention_details tool to retrieve the full content and metadata for a specific mention found by Determ.

Is real-time monitoring supported?

Yes, the list_media_mentions tool retrieves the most recent mentions based on your query settings, providing real-time data from the Determ platform.

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

Name: Determ
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Determ through Vinkius, pass the Edge URL in the `mcps` parameter and every Determ 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="Determ Specialist",
    goal="Help users interact with Determ effectively",
    backstory=(
        "You are an expert at leveraging Determ 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 Determ "
        "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 Determ MCP Server

Integrate Determ (formerly Mediatoolkit), the powerful media monitoring and social listening platform, directly into your AI workflow. Track brand mentions across the web and social media, analyze sentiment trends, and monitor your competitive landscape using natural language.

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

Mention Monitoring — List and retrieve real-time media mentions for your keywords and topics from over 100 million sources.
Sentiment Intelligence — Retrieve a breakdown of sentiment (positive, neutral, negative) for any of your monitoring queries.
Query Management — List and review your configured monitoring queries and their specific settings.
Analytics Reporting — Access metadata for your media monitoring and analytics reports directly via chat.

The Determ 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 Determ to CrewAI via MCP

Follow these steps to integrate the Determ 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 Determ

Why Use CrewAI with the Determ MCP Server

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

Determ + CrewAI Use Cases

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

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

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

Determ MCP Tools for CrewAI (10)

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

get_account_metadata

Retrieve settings and limits for your Determ account

get_mention_details

Get full content and technical metadata for a specific media mention

get_monitoring_query_details

Get detailed settings and status for a specific monitoring query

get_query_sentiment_summary

Retrieve a breakdown of sentiment (positive, neutral, negative) for a specific query

list_analytics_reports

List all available analytics and media monitoring reports

list_media_mentions

List recent media mentions for a specific monitoring query

list_monitoring_queries

List all media monitoring queries (keywords/topics) in your Determ account

list_recent_high_reach_mentions

List only the mentions with the highest estimated reach

list_top_media_sources

Identify the media sources with the highest volume of mentions (mock logic)

search_mentions_by_keyword

Search for specific keywords within the mentions of a monitoring query

Example Prompts for Determ in CrewAI

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

"List my active monitoring queries."

"Show me the sentiment breakdown for the 'Main Competitor' query."

"What are the top media sources for 'Industry Trends'?"

Troubleshooting Determ MCP Server with CrewAI

Common issues when connecting Determ 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.

Determ + CrewAI FAQ

Common questions about integrating Determ 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.