How to Use the Custify MCP in LlamaIndex

Q: Is it possible to query Custify metrics via LlamaIndex?

You can call listcustomerkpis directly through the tool spec. The results are then ingested by your agent to ground its response in actual account data.

Ground your LlamaIndex RAG applications in real-time Custify customer data.

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Connect Custify MCP to LlamaIndex

Create your Vinkius account to connect Custify 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 Custify with LlamaIndex

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Index Custify records for LlamaIndex

Convert `list_companies` results into vector embeddings for semantic search. You query your entire customer base using natural language instead of rigid filters. Your RAG application stays current because it pulls directly from the source. The agent retrieves fresh metrics during the query process to prevent stale answers.

Ground LlamaIndex answers in API data

Force your agent to use `list_customer_kpis` to find exact threshold values. This prevents the model from guessing performance numbers when it should be reading them. By combining live API results with your local documents, you build a smarter knowledge base. The agent references specific customer health scores to justify its conclusions.

Filter Custify data with allowed_tools

Restrict your LlamaIndex agent to a specific subset of tools like `search_customers_by_keyword`. You define the boundaries of what the agent can access. This keeps your index clean and focused on relevant account information. You maintain control over which parts of the Custify API remain reachable.

Setup guide

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

You use the MCP tool spec to wrap the server endpoints. This allows your LlamaIndex agent to treat CRM data as queryable functions.

Absolutely. You can fetch lists of customers and index them into your vector store. The agent then retrieves this data to answer questions about customer churn.

You can call `list_customer_kpis` directly through the tool spec. The results are then ingested by your agent to ground its response in actual account data.

Schedule an agent task to call the listing tools periodically. The returned data is ready to be embedded and added to your index.

All traffic is encrypted in transit and handled via a single token. The server only accesses your customer contact details and success metrics, with no persistent storage of your PII.

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