How to Use the Xiaoshouyi / Neocrm MCP in LlamaIndex

Build knowledge-augmented apps for Xiaoshouyi / Neocrm using LlamaIndex.

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Connect Xiaoshouyi / Neocrm MCP to LlamaIndex

Create your Vinkius account to connect Xiaoshouyi / Neocrm 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 Xiaoshouyi / Neocrm with LlamaIndex

Ask AI about this MCP

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Perplexity

Search past client interactions.

Instead of just calling `list_contacts`, you index the results. This lets your RAG app answer questions like, 'What was discussed with John Smith last quarter?' The knowledge base grounds answers in actual CRM data from Neocrm, meaning no hallucinations.

Analyze historical sales opportunities.

The unique power here is that `list_opportunities` output becomes searchable context. You can query the index to understand why a deal stalled or what its initial scope was. This builds a powerful knowledge layer over your existing sale pipeline records.

Audit account and user structures.

You don't just list accounts using `list_accounts`; you query them. The index allows you to ask, 'Which users are associated with the Acme Corp account?' It combines data from both `list_users` and `list_accounts` into one searchable knowledge graph.

Setup guide

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

LlamaIndex indexes the results. You pass the output from tools like `list_leads` into a vector store, turning raw API data into searchable knowledge that your agent can query.

The server exposes leads, contacts, accounts, and opportunities. The index absorbs this structured data, allowing you to retrieve semantic answers based on the actual records.

Yeah, it changes the game. Instead of getting a list that requires filtering, you ask a question, and the system retrieves an answer grounded in the context of your CRM data.

Use it when you need to query historical patterns. For instance, instead of listing all tasks (`list_tasks`), you ask: 'What were the top three reasons we missed deadlines last month?'

The server touches personal identifiable information (PII) like contact names, email addresses, and phone numbers. Indexing this requires careful management of access permissions.

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