Kylas MCP Server for LlamaIndexGive LlamaIndex instant access to 7 tools to Create Contact, Create Lead, Get Lead, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Kylas 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 Kylas app connector for LlamaIndex is a standout in the Sales Automation category — giving your AI agent 7 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 Kylas. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Kylas?"
)
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 Kylas MCP Server
Connect your Kylas account to any AI agent and manage your sales CRM through natural conversation.
LlamaIndex agents combine Kylas tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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, create, and inspect leads with status tracking
- Deal Pipeline — Browse deals across pipeline stages with values
- Contact Database — Manage contacts with activity and communication history
- Pipeline Monitoring — Track conversion rates and deal velocity
The Kylas MCP Server exposes 7 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 7 Kylas tools available for LlamaIndex
When LlamaIndex connects to Kylas through Vinkius, your AI agent gets direct access to every tool listed below — spanning pipeline-management, deal-tracking, lead-management, 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 contact
Pass data as a JSON string. Create a new lead
Get specific lead details
List all CRM contacts
List all CRM deals
List all Kylas leads
List CRM tasks
Connect Kylas to LlamaIndex via MCP
Follow these steps to wire Kylas 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 Kylas MCP Server
LlamaIndex provides unique advantages when paired with Kylas through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Kylas tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Kylas tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Kylas, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Kylas tools were called, what data was returned, and how it influenced the final answer
Kylas + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Kylas MCP Server delivers measurable value.
Hybrid search: combine Kylas real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Kylas 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 Kylas for fresh data
Analytical workflows: chain Kylas queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Kylas in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Kylas immediately.
"Show the sales pipeline and deals closing this week."
"Create a new lead and show all contacts at acmecorp.com."
"Show team performance and pipeline conversion metrics."
Troubleshooting Kylas MCP Server with LlamaIndex
Common issues when connecting Kylas to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpKylas + LlamaIndex FAQ
Common questions about integrating Kylas MCP Server with LlamaIndex.