How to Use the Dub.co MCP in LlamaIndex

Q: Can LlamaIndex query Dub.co click metrics semantically?

Yes, by using getworkspaceanalytics within a RAG pipeline, the agent retrieves raw metrics, converts them into text nodes, and indexes them. Users can then ask conversational questions about which campaigns performed best.

Q: Can I use this MCP Server to clean up dead links in LlamaIndex?

Absolutely. Your agent can run listlinks to identify outdated targets, cross-reference them with your vector database, and execute deleteshortlink to remove them from your active workspace.

Index your Dub.co analytics and short links directly into LlamaIndex vector stores for hallucination-free querying.

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Connect Dub.co MCP to LlamaIndex

Create your Vinkius account to connect Dub.co to LlamaIndex 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 Dub.co with LlamaIndex

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Build RAG pipelines with Dub.co analytics

`get_workspace_analytics` pulls raw performance metrics that your LlamaIndex pipeline indexes directly into a vector store. This lets you query past campaign performance using semantic search instead of writing custom SQL queries. Your agent retrieves click counts, browser distributions, and geographic data to ground its answers in actual performance metrics. You get accurate, data-backed reports because the model reads directly from your indexed analytics history.

Query link metadata using LlamaIndex agents

`get_link_details` fetches the exact destination URL, tag associations, and creation dates for any short link in your workspace. LlamaIndex uses this tool to ingest live metadata, turning your short link registry into a searchable document index. This live connection prevents your agent from hallucinating old redirect targets. The agent queries the current state of your links before answering questions about active marketing paths.

Manage active domains with this MCP Server

`list_domains` returns your active brand domains so your LlamaIndex indexer can verify which hostnames are valid during document ingestion. The pipeline cross-references your raw data files with your live web configurations. This verification step ensures that any generated short links use authorized brand domains. Your agent checks the live registry before suggesting new redirection configurations to your marketing team.

Setup guide

Set up Dub.co MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Dub.co MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Dub.co tools.",
)
response = await agent.run("List recent Dub.co data")

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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 Dub.co. 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 Dub.co MCP in LlamaIndex

You initialize the BasicMCPClient and convert the server tools into a LlamaIndex tool spec. From there, your agent can call `list_links` to fetch your entire registry and load the metadata into your vector index.

Yes, by using `get_workspace_analytics` within a RAG pipeline, the agent retrieves raw metrics, converts them into text nodes, and indexes them. Users can then ask conversational questions about which campaigns performed best.

The framework manages execution loops, but you should configure chunk sizes when running bulk queries with `list_links`. If you hit rate limits, the server returns standard error codes that your agent can catch and retry.

Absolutely. Your agent can run `list_links` to identify outdated targets, cross-reference them with your vector database, and execute `delete_short_link` to remove them from your active workspace.

It only exposes the specific link metadata, analytics metrics, and domain lists allowed by your API key. No underlying customer database tables or personal identification records are accessed, keeping your workspace secure.

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