Close MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Lead, Get Current User, Get Lead Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Close as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Close app connector for LlamaIndex is a standout in the Communication Messaging category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Close. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Close?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Close MCP Server
Connect your Close CRM account to any AI agent and take full control of your sales workflows through natural conversation.
LlamaIndex agents combine Close tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Lead Management — List all leads in your pipeline and retrieve full company profiles with contacts, custom fields, and activity history
- Lead Creation — Add new leads directly from conversation, including company name and website URL
- Opportunity Tracking — Monitor your active deals with stage, value, and expected close dates
- Task Management — Review pending and completed CRM tasks to stay on top of follow-ups
- User Context — Retrieve your authenticated user profile to understand your current permissions and role
The Close MCP Server exposes 6 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 6 Close tools available for LlamaIndex
When LlamaIndex connects to Close through Vinkius, your AI agent gets direct access to every tool listed below — spanning lead-management, pipeline-tracking, inside-sales, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new lead
Get information about the authenticated API user
Get details of a specific lead
List CRM tasks
List all leads in Close CRM
List sales opportunities
Connect Close to LlamaIndex via MCP
Follow these steps to wire Close into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Close MCP Server
LlamaIndex provides unique advantages when paired with Close through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Close tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Close tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Close, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Close tools were called, what data was returned, and how it influenced the final answer
Close + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Close MCP Server delivers measurable value.
Hybrid search: combine Close real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Close to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Close for fresh data
Analytical workflows: chain Close queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Close in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Close immediately.
"List all my leads in Close and highlight the ones added this week."
"Create a new lead for the company 'Nordic AI Labs' with their website nordicailabs.com."
"Show my active sales opportunities and any overdue tasks I need to handle."
Troubleshooting Close MCP Server with LlamaIndex
Common issues when connecting Close to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpClose + LlamaIndex FAQ
Common questions about integrating Close MCP Server with LlamaIndex.