Daktela MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Contact, Create Ticket, Get Me, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Daktela 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 Daktela app connector for LlamaIndex is a standout in the Communication Messaging category — giving your AI agent 12 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 Daktela. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Daktela?"
)
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 Daktela MCP Server
Connect your Daktela omnichannel contact center to any AI agent and simplify how you coordinate customer support, track communication history, and manage CRM records through natural conversation.
LlamaIndex agents combine Daktela tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Ticket Lifecycle — Create, list, and query support tickets and cases to ensure customer issues are resolved promptly.
- Omnichannel Activities — Monitor real-time and past activities across calls, emails, and chats within your center.
- CRM Control — List and create contacts and accounts (companies) to maintain an organized customer directory.
- Call & Email History — Retrieve detailed logs of past phone interactions and email threads for audit and reporting.
- Team & Queue Coordination — List configured queues and system users to manage agent distribution effectively.
- Profile Oversight — Fetch your authenticated user profile and verify system configurations directly from the agent.
The Daktela MCP Server exposes 12 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 12 Daktela tools available for LlamaIndex
When LlamaIndex connects to Daktela through Vinkius, your AI agent gets direct access to every tool listed below — spanning omnichannel, contact-center, voip, 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 CRM contact
Create a new ticket
Get current user information
Get details of a specific ticket
List CRM accounts
List recent activities in Daktela
List call history
List CRM contacts
List email history
List contact center queues
List support tickets
List Daktela users
Connect Daktela to LlamaIndex via MCP
Follow these steps to wire Daktela 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 Daktela MCP Server
LlamaIndex provides unique advantages when paired with Daktela through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Daktela tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Daktela tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Daktela, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Daktela tools were called, what data was returned, and how it influenced the final answer
Daktela + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Daktela MCP Server delivers measurable value.
Hybrid search: combine Daktela real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Daktela 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 Daktela for fresh data
Analytical workflows: chain Daktela queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Daktela in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Daktela immediately.
"List all active activities in the contact center."
"Create a support ticket: 'Login issue' for contact 'cont_10293'."
"Show me the email history for contact 'cont_5521'."
Troubleshooting Daktela MCP Server with LlamaIndex
Common issues when connecting Daktela to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDaktela + LlamaIndex FAQ
Common questions about integrating Daktela MCP Server with LlamaIndex.