How to Use the Moz (SEO Metrics & Link Research) MCP in AutoGen
Let AutoGen agents debate backlink profiles and domain metrics using live Moz API data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Moz (SEO Metrics & Link Research) MCP to AutoGen
Create your Vinkius account to connect Moz (SEO Metrics & Link Research) to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Run Multi-Agent Moz Audits In AutoGen
`get_url_metrics` provides the baseline Domain Authority and spam scores that your AutoGen agents debate. A specialized SEO audit agent can pull these metrics, while a separate risk-assessment agent challenges the spam scores. This multi-agent debate ensures you don't make critical domain acquisition decisions based on a single metric. By integrating this MCP Server, your agents negotiate the final strategy using live, verifiable data. Fix it before buying dead domains.
Evaluate Backlinks Through Agent Debates
`get_incoming_links` fetches the live backlink profile of any target domain for your AutoGen agents to analyze. One agent can focus on finding high-authority links, while another flags low-quality referring domains. They can cooperatively run `get_top_links` to isolate the most valuable linking assets on a competitor's domain. The final consensus report is compiled only after both agents agree on the quality of the link profile.
Analyze Anchor Text Distribution Cooperatively
`get_anchor_text` lets your AutoGen agents inspect literal anchor text distributions to spot over-optimization patterns. A content agent can review the text relevance while an SEO agent checks for manipulative keyword stuffing. If they detect anomalies, they can call `get_outgoing_links` to trace where the target domain is pointing its external equity. This cooperative analysis prevents your team from buying domains with toxic link profiles.
Set up Moz (SEO Metrics & Link Research) MCP in AutoGen
Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]package - Active Vinkius subscription with a valid endpoint token
- 1
Install AutoGen with MCP
Run
pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includesmcp_server_toolsfor stateless tool access. - 2
Fetch tools from the MCP
Call
mcp_server_tools(SseServerParams(url=...))with your Vinkius endpoint. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. - 3
Run your agent
Pass the tools to
AssistantAgentand callagent.run(). The agent invokes Moz (SEO Metrics & Link Research) tools and returns structured results.
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
tools = await mcp_server_tools(server_params)
agent = AssistantAgent(
name="Moz (SEO Metrics & Link Research)_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Moz (SEO Metrics & Link Research) data")
print(result.messages[-1].content) Prerequisites
- Python 3.10+ installed
-
autogen-ext[mcp]+autogen-agentchat - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Same packages as above.
McpWorkbenchis ideal when your agent needs stateful sessions across multiple tool calls. - 2
Use McpWorkbench as context manager
Wrap your agent in
async with McpWorkbench(...)to maintain shared state and resources. The workbench manages the full MCP session lifecycle. - 3
Run with workbench
Pass
workbench=workbenchto your agent. State is preserved across multiple tool calls within the same session.
from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
server_params = SseServerParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
async with McpWorkbench(server_params) as workbench:
agent = AssistantAgent(
name="Moz (SEO Metrics & Link Research)_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Moz (SEO Metrics & Link Research) data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Moz. 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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