HighLevel MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add HighLevel 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 HighLevel. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in HighLevel?"
)
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 HighLevel MCP Server
Connect your HighLevel (GoHighLevel) account to any AI agent and take full control of your sales pipeline, contact management, and scheduling through natural conversation.
LlamaIndex agents combine HighLevel tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Contact Oversight — Perform advanced searches for leads, retrieve full profiles, and create new contact records effortlessly.
- Sales Pipelines — List pipelines and search for opportunities to monitor your deals and revenue flow.
- Appointment Management — Access your calendars, check for free slots in real-time, and book appointments directly from the chat.
- Task Coordination — List and create tasks for specific contacts to ensure follow-ups are never missed.
- Location Tracking — Retrieve location-specific tags to categorize and filter your data accurately.
- Unified CRM — Bridge the gap between your marketing and sales activities using the powerful API v2.
The HighLevel MCP Server exposes 11 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.
How to Connect HighLevel to LlamaIndex via MCP
Follow these steps to integrate the HighLevel MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 11 tools from HighLevel
Why Use LlamaIndex with the HighLevel MCP Server
LlamaIndex provides unique advantages when paired with HighLevel through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine HighLevel tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain HighLevel tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query HighLevel, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what HighLevel tools were called, what data was returned, and how it influenced the final answer
HighLevel + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the HighLevel MCP Server delivers measurable value.
Hybrid search: combine HighLevel real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query HighLevel 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 HighLevel for fresh data
Analytical workflows: chain HighLevel queries with LlamaIndex's data connectors to build multi-source analytical reports
HighLevel MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect HighLevel to LlamaIndex via MCP:
create_appointment
Book a new appointment on a calendar
create_contact
Pass payload as JSON string in "body_json" (requires firstName, email, or phone). Add a new contact/lead to HighLevel
create_contact_task
Assign a new task to a specific contact
get_calendar_free_slots
Check availability for a specific calendar
get_contact_details
Get detailed information for a specific contact
list_calendars
List all calendars available for a location
list_contact_tasks
List all tasks assigned to a specific contact
list_location_tags
List all custom tags for a location
list_pipelines
List sales pipelines for a specific location
search_contacts
Pass search criteria as a JSON string in "search_json". Search for contacts in HighLevel
search_opportunities
Search for opportunities within a pipeline
Example Prompts for HighLevel in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with HighLevel immediately.
"Search for contact 'John Doe' and show his pending tasks."
"Find free slots on the 'Sales Consultation' calendar for next Monday."
"Show me all opportunities in the 'Product Sales' pipeline."
Troubleshooting HighLevel MCP Server with LlamaIndex
Common issues when connecting HighLevel to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHighLevel + LlamaIndex FAQ
Common questions about integrating HighLevel MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect HighLevel with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect HighLevel to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.