How to Use the Sansan MCP in LlamaIndex

Q: Does this MCP Server support LlamaIndex filtering?

Yes. You can use the allowedtools filter to restrict which contacts the agent can access. It keeps your data retrieval precise.

Q: Can I index Sansan tags with LlamaIndex?

You can use listtags to categorize your contacts. These tags become metadata in your index, allowing for filtered searches.

Index your Sansan contact network into LlamaIndex for grounded, retrieval-augmented generation and semantic analysis.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Sansan MCP to LlamaIndex

Create your Vinkius account to connect Sansan to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Sansan with LlamaIndex

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Index Sansan contacts for LlamaIndex RAG

Feed results from `list_biz_cards` into your vector store. Your agent then queries your network using semantic meaning rather than exact keywords. This turns your contact list into a searchable brain. The agent retrieves relevant details from your history instead of guessing.

Ground AI answers in Sansan data

Use `get_person` to pull specific details during the retrieval phase. Your agent provides answers based on the actual contact records it finds. This eliminates hallucinations. The agent cites the data retrieved from the server, giving you a reliable trail for every response.

Query your network via the MCP Server interface

Run `search_biz_cards` to find specific leads within your LlamaIndex workflow. The tool output is immediately indexed for further analysis. You avoid manual lookups by letting your agent navigate the API. It finds the right card and extracts the necessary contact info in one go.

Setup guide

Set up Sansan 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 Sansan 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 Sansan tools.",
)
response = await agent.run("List recent Sansan data")

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