Dixa MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Dixa 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 Dixa. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Dixa?"
)
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 Dixa MCP Server
Integrate Dixa, the customer friendship platform, directly into your AI workflow. Manage your multi-channel support conversations, monitor agent presence and performance, track service queues, and oversee your support teams using natural language.
LlamaIndex agents combine Dixa tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Conversation Oversight — List and retrieve detailed information for all customer conversations and their current processing status.
- Agent Intelligence — Monitor real-time agent presence, profile details, and team assignments across your organization.
- Queue Monitoring — Track active service queues and routing settings to ensure efficient support delivery.
- Team Management — List all support teams and identify members assigned to specific organizational units.
The Dixa MCP Server exposes 10 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 Dixa to LlamaIndex via MCP
Follow these steps to integrate the Dixa 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 10 tools from Dixa
Why Use LlamaIndex with the Dixa MCP Server
LlamaIndex provides unique advantages when paired with Dixa through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Dixa tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Dixa tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Dixa, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Dixa tools were called, what data was returned, and how it influenced the final answer
Dixa + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Dixa MCP Server delivers measurable value.
Hybrid search: combine Dixa real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Dixa 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 Dixa for fresh data
Analytical workflows: chain Dixa queries with LlamaIndex's data connectors to build multi-source analytical reports
Dixa MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Dixa to LlamaIndex via MCP:
get_agent_profile
Get full profile and performance data for a specific agent
get_conversation_details
Get detailed information for a specific customer conversation
get_service_account_metadata
Retrieve metadata and usage limits for your Dixa account
list_customer_conversations
List all customer service conversations in your Dixa account
list_open_support_tickets
Identify conversations that are currently in an "Open" or "Unassigned" status
list_service_agents
List all support agents registered in your Dixa organization
list_service_queues
List all active service queues configured in Dixa
list_support_teams
List all configured support teams and their members
quick_agent_presence_audit
Retrieve a high-level summary of active agent presence statuses
search_conversations_by_subject
Search for conversations using a keyword in the subject
Example Prompts for Dixa in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Dixa immediately.
"List all open support conversations."
"Show me the details for conversation '12345'."
"Who is currently available in the 'Sales' team?"
Troubleshooting Dixa MCP Server with LlamaIndex
Common issues when connecting Dixa to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDixa + LlamaIndex FAQ
Common questions about integrating Dixa 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 Dixa 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 Dixa to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.