Can I search for local businesses in a specific city through the agent?

Yes. The `search_google_maps` tool allows your AI agent to retrieve local business listings, including their ratings, physical addresses, and contact info, helping you perform local market research through chat.

How do I get product prices from Google Shopping via conversation?

You can use the `search_google_shopping` tool. Simply provide the product name, and Zenserp will return a structured list of vendor prices and availability to help you audit the e-commerce landscape.

Is it possible to search on Bing or DuckDuckGo using this server?

Absolutely. This server includes specialized tools like `search_bing_organic` and `search_duckduckgo_organic`, allowing your agent to retrieve results from multiple search engines for broader data coverage.

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

Name: Zenserp
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Connect your Zenserp account to any AI agent and harness the power of real-time search intelligence through natural conversation.

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

Organic Search — Retrieve structured organic results from Google, Bing, Yandex, and DuckDuckGo including titles, URLs, and snippets
Image Discovery — Find high-quality images and retrieve direct source or thumbnail URLs across the major search engines
Local Intelligence — Search Google Maps for business listings, physical addresses, ratings, and reviews for any location
News Monitoring — Retrieve breaking stories and current articles from Google News with precise timestamps and source metadata
E-commerce Auditing — Compare product prices and availability by scraping Google Shopping results into structured JSON
Video Search — Find indexed videos across various platforms through Google Video and YouTube search tools
Geographic Precision — Execute searches with specific location parameters (e.g., 'New York, NY') to see localized results

The Zenserp 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 Zenserp to CrewAI via MCP

Follow these steps to integrate the Zenserp 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 Zenserp

Why Use CrewAI with the Zenserp MCP Server

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

Zenserp + CrewAI Use Cases

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

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

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

Zenserp MCP Tools for CrewAI (10)

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

search_bing

Retrieves organic search results from Microsoft Bing

search_duckduckgo

Retrieves organic search results from DuckDuckGo

search_google

Provide a query string and optional location (e.g. "New York,NY"). Retrieves organic search results from Google

search_images

Retrieves image search results from Google

search_maps

Retrieves local business listings and reviews from Google Maps

search_news

Returns articles with titles, snippets, and timestamps. Retrieves current news articles from Google News

search_shopping

Retrieves product prices and availability from Google Shopping

search_videos

Retrieves video search results from Google Video search

search_yandex

Retrieves search results from the Yandex search engine

search_youtube

Retrieves search results directly from the YouTube platform

Example Prompts for Zenserp in CrewAI

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

"Search Google for 'best CRM software for small business' and show me the top 5 organic results."

"Find restaurants in 'Austin, TX' using Google Maps and show their ratings."

"What are the current news headlines for 'generative AI'?"

Troubleshooting Zenserp MCP Server with CrewAI

Common issues when connecting Zenserp 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.

Zenserp + CrewAI FAQ

Common questions about integrating Zenserp 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.