Keap 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 Keap as an MCP tool provider through the 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 Keap. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Keap?"
)
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 Keap MCP Server
Connect your Keap (formerly Infusionsoft) account to any AI agent to optimize your CRM and sales workflows. This MCP server enables your agent to interact with contacts, tags, and automation campaigns directly from natural language interfaces.
LlamaIndex agents combine Keap tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through the 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 Management — List, retrieve, and create contact profiles to maintain your lead database
- Marketing Automation — List and monitor active campaigns and automation sequences
- Segmentation — Manage tags and apply them to contacts to trigger specific workflows
- Sales Pipeline — Query opportunities and deals to track your revenue growth
- Billing Visibility — Access invoices and orders to stay on top of customer transactions
The Keap 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 Keap to LlamaIndex via MCP
Follow these steps to integrate the Keap 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 Keap
Why Use LlamaIndex with the Keap MCP Server
LlamaIndex provides unique advantages when paired with Keap through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Keap tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Keap tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Keap, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Keap tools were called, what data was returned, and how it influenced the final answer
Keap + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Keap MCP Server delivers measurable value.
Hybrid search: combine Keap real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Keap 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 Keap for fresh data
Analytical workflows: chain Keap queries with LlamaIndex's data connectors to build multi-source analytical reports
Keap MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Keap to LlamaIndex via MCP:
apply_tag_to_contact
Apply a tag to a specific contact
create_contact
Requires at least a first name or email. Create a new contact in Keap
get_business_profile
Get Keap business profile information
get_contact
Get details for a specific contact
list_campaigns
List all marketing campaigns
list_contacts
Use this to search for leads or customers. List all contacts in Keap
list_invoices
List all invoices
list_opportunities
List sales opportunities
list_orders
List ecommerce orders
list_tags
List all available tags
list_users
List all application users
Example Prompts for Keap in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Keap immediately.
"Find a contact with email 'john@example.com' in Keap."
"Show me all my available tags in Keap."
"List my recent ecommerce orders."
Troubleshooting Keap MCP Server with LlamaIndex
Common issues when connecting Keap to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKeap + LlamaIndex FAQ
Common questions about integrating Keap 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 Keap 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 Keap to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.