How to Use the Mozscape MCP in LangChain

Q: Can I filter link profiles by specific anchor text?

Yes. Your agent can use filterlinksbyanchor or v2anchortext to isolate specific brand terms or spam signals in your link profile.

Get raw Mozscape link equity metrics directly into your LangChain reasoning loops to build self-correcting SEO pipelines.

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Connect Mozscape MCP to LangChain

Create your Vinkius account to connect Mozscape to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Mozscape with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build self-correcting LangChain SEO pipelines

LangChain agents can execute complex multi-step reasoning by linking Mozscape metrics together. Your agent can run `fetch_site_metrics` to flag low-authority pages, then immediately trigger `list_linking_domains` to diagnose the root cause of the drop. Because LangChain handles state across tool chains, the output of `v2_url_metrics` feeds directly into the next prompt. You don't write glue code. The agent decides when to pull backlink profiles or check redirect paths on its own.

Track Mozscape MCP Server calls in LangSmith

Stop guessing why your link-building agent spent your API budget. LangSmith traces every call routed through this MCP connection to `fetch_link_status` and `v2_link_intersect` so you can see the exact context your agent used before making a decision. This deep observability exposes latency bottlenecks and token usage for complex runs. You will see exactly how your agent parsed the output of `filter_links_by_anchor` to verify if a backlink is live and passing equity.

Prevent API overages in sequential runs

Running autonomous agents can destroy your API limits if you aren't careful. This MCP integration lets your LangChain agent run `lookup_quota` or `v2_usage_data` before kicking off a massive site audit. If the remaining quota is too low, the agent can dynamically switch from bulk checks like `fetch_multiple_site_metrics` to targeted single-URL scans. This keeps your search operations running without surprise bills.

Setup guide

Set up Mozscape MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Mozscape tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "mozscape-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Mozscape transactions"
    })
    print(result["messages"][-1].content)

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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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Common questions about Mozscape MCP in LangChain

You should configure LangChain's retry logic around the MCP tool calls. When tools like `fetch_multiple_site_metrics` hit limits, the framework handles backoff before the agent fails.

Yes, easily. You can pass the tools from this server alongside a database tool, allowing the agent to fetch DA via `fetch_site_metrics` and write it directly to your SQL database.

LangChain runs these tools statelessly by default, but you can use session context. This is useful when comparing old and new metrics via `v2_url_metrics` across a multi-turn conversation.

Yes. Your agent can use `filter_links_by_anchor` or `v2_anchor_text` to isolate specific brand terms or spam signals in your link profile.

Vinkius runs this MCP Server in an isolated sandbox, meaning your API credentials and the raw URL metrics fetched via `v2_url_metrics` never persist on our servers or leak to other tenants.

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