How to Use the Surfer SEO MCP in CrewAI

Q: How does Surfer SEO fit into crewai for multi-agent tasks?

Assign different roles: one agent runs createseoaudit() to gather data, and another uses the resulting details via getauditdetails() to write the content plan. The agents collaborate automatically.

Q: What is the best way to use Surfer SEO with crewai?

Use a 'Discovery Agent' that first runs createserpanalyzer() and passes those ranking factors to an 'Implementation Agent,' which then calls getcontenteditordetails() to refine the content.

Automate multi-agent SEO operations using the crewai framework.

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Connect Surfer SEO MCP to CrewAI

Create your Vinkius account to connect Surfer SEO to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Surfer SEO with CrewAI

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Agent research with crewai and Surfer SEO

Assign one agent to act as a 'Keyword Researcher.' This agent's job is to call `create_serp_analyzer()` for specific target keywords. It gathers raw SERP data, which it then passes to the next agent in the workflow. The subsequent 'Analysis Agent' uses this gathered data and calls `get_prominent_terms()` to pull out actionable phrases. The agents work together, ensuring comprehensive keyword coverage.

Structured content creation with crewai

You can set up a specialized 'Content Editor Agent.' This agent receives the desired topic from a manager and then uses `create_content_editor()` to generate an initial query. It then monitors progress by calling `get_content_score()` until the score is optimal. The shared memory between agents means that when the final 'Reviewer Agent' steps in, it has access to the entire history of queries and scores.

Orchestrating full audits with crewai

Assign a dedicated agent to handle site maintenance. This agent uses `create_seo_audit()` for specific URLs across different regions. The workflow can then run parallel checks, listing all results using `list_seo_audits()`. The moderator agent monitors the entire process, ensuring that every single page on the target domain gets audited before reporting completion.

Setup guide

Set up Surfer SEO MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Surfer SEO tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Surfer SEO Analyst",
    goal="Access and analyze Surfer SEO data via MCP.",
    backstory="Expert analyst with direct Surfer SEO access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Surfer SEO transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Surfer SEO Analyst",
        goal="Access and analyze Surfer SEO data via MCP.",
        backstory="Expert analyst with direct Surfer SEO access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Surfer SEO transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Surfer SEO. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Surfer SEO MCP in CrewAI

Assign different roles: one agent runs `create_seo_audit()` to gather data, and another uses the resulting details via `get_audit_details()` to write the content plan. The agents collaborate automatically.

Use a 'Discovery Agent' that first runs `create_serp_analyzer()` and passes those ranking factors to an 'Implementation Agent,' which then calls `get_content_editor_details()` to refine the content.

Yes. You can build a loop where a monitoring agent periodically runs `list_content_editors()` and checks scores with `get_content_score()`, making sure the content stays highly ranked.

Absolutely. The shared memory allows all agents to see the full picture—from initial audit results to final prominent terms, keeping the process transparent and traceable.

This server processes structured text strings including content guidelines, SERP search results, and optimization scores.

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