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How to Use the Clientify MCP in LlamaIndex

Index your Clientify CRM data into LlamaIndex vector stores to ground your agent in real sales context.

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LlamaIndex

Connect Clientify MCP to LlamaIndex

Create your Vinkius account to connect Clientify 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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Ground RAG queries in live CRM data with this MCP Server

The `list_contacts` tool retrieves your customer directory so LlamaIndex can index it for semantic search. Instead of guessing, your agent queries this index to find specific customer details. This setup prevents hallucinations by forcing the model to read directly from your Clientify records. You get answers based on actual, live CRM data.

Track active sales opportunities

The `list_deals` tool pulls your active pipeline status directly into your LlamaIndex knowledge base. Your agent uses this data to answer complex questions about your current sales forecast. You can filter these results using the `list_pipelines` tool to isolate specific sales stages. This keeps your vector store updated with fresh pipeline movements.

Log customer interactions instantly

The `create_activity` tool writes new tasks and notes back to Clientify based on your RAG pipeline outputs. When a user asks a question, your LlamaIndex agent answers and logs the interaction. This loop ensures your CRM stays updated without manual data entry. The agent handles the writing while you focus on the conversation.

Setup guide

Set up Clientify MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

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

  2. 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. 3

    Convert to LlamaIndex tools

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

  4. 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 Clientify tools.",
)
response = await agent.run("List recent Clientify data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Clientify. 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.

Why Choose Vinkius

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Real-time monitoring

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visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

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lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Clientify MCP in LlamaIndex

Use the BasicMCPClient to connect to your Vinkius endpoint, then wrap it in an McpToolSpec. This makes all ten Clientify tools available to your LlamaIndex FunctionAgent.
Yes, by combining `list_contacts` with a LlamaIndex vector store index. Your agent pulls the contacts, embeds them, and runs semantic queries on your CRM data.
It exposes ten critical tools for managing your CRM. You can read, write, and update contacts, deals, and activities using this MCP Server.
The `update_contact` tool allows your agent to modify existing records. If a customer's email or phone number changes during a chat, the agent updates Clientify instantly.
All transactions pass through a secure, single-token endpoint managed by Vinkius. Your CRM data, including emails and deal values, is processed in a temporary sandbox that never stores your credentials or payloads.

Start using the Clientify MCP today

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