How to Use the Landing MCP in LlamaIndex

Q: How do I load Landing tools into LlamaIndex?

Install llama-index-tools-mcp. Create a BasicMCPClient, wrap it in an McpToolSpec, and call totoollistasync() to pass the endpoints to your FunctionAgent.

Q: Can LlamaIndex filter which Landing tools are available?

Yes. You can use the allowedtools parameter to restrict your agent. For example, you might only give it access to listlandingpages and hide the webhook deletion tools for safety.

Q: How does LlamaIndex handle Landing lead data?

When your agent calls listlandingleads, it can either process the JSON directly in memory or index the results into your vector store for future semantic queries.

Turn your marketing campaigns into a queryable knowledge base. Give LlamaIndex direct access via this MCP Server.

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Connect Landing MCP to LlamaIndex

Create your Vinkius account to connect Landing 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 Landing with LlamaIndex

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Index Landing data with LlamaIndex

Landing marketing data rots in dashboards. The Landing MCP Server changes that by letting your LlamaIndex application pull live API data straight into your vector store. You run `list_landing_projects` and instantly index every active campaign. Now you chat with your actual marketing infrastructure. When you ask your RAG application about recent conversions, it queries the index, retrieves the exact records from `list_landing_leads`, and gives you a grounded answer without hallucinating numbers.

Ground answers in live campaign state

Static Landing documents go out of date the minute you embed them. By connecting this MCP Server, your RAG setup fetches real-time state. If a user asks which pages are live, the agent calls `list_landing_pages` before generating the response. This means your internal tools always reflect reality. The agent verifies routing rules by checking `list_landing_webhooks` to confirm exactly where your event data flows right now.

Manage infrastructure through search

RAG doesn't have to be read-only for your Landing account. Your LlamaIndex function agent searches your knowledge base to find a specific campaign, then takes action on it. It uses `create_landing_webhook` to set up a new integration based on a natural language request. If a project gets deprecated, the agent cleans up. It finds the obsolete routes in the index and executes `delete_landing_webhook`. You build a system that manages itself.

Setup guide

Set up Landing 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 Landing 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 Landing tools.",
)
response = await agent.run("List recent Landing 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 Landing. 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 Landing MCP in LlamaIndex

Install `llama-index-tools-mcp`. Create a `BasicMCPClient`, wrap it in an `McpToolSpec`, and call `to_tool_list_async()` to pass the endpoints to your FunctionAgent.

Yes. You can use the `allowed_tools` parameter to restrict your agent. For example, you might only give it access to `list_landing_pages` and hide the webhook deletion tools for safety.

When your agent calls `list_landing_leads`, it can either process the JSON directly in memory or index the results into your vector store for future semantic queries.

LlamaIndex catches the timeout error from the tool execution. You should configure your FunctionAgent with retry logic if you expect heavy load on the `list_landing_projects` endpoint.

The server processes sensitive PII from your captured leads. We run this integration inside an ephemeral, zero-trust sandbox. The data only moves between the API and your LlamaIndex environment, nowhere else.

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