Chaport MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Chaport as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Chaport. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Chaport?"
)
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 Chaport MCP Server
Connect your Chaport account to any AI agent and take full control of your customer messaging operations through natural conversation. Streamline how you engage with website visitors and manage your support team.
LlamaIndex agents combine Chaport tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Live Messaging — Send and receive messages in active chat sessions natively
- Visitor Intelligence — List and retrieve details for recent website visitors and their contact info flawlessly
- Conversation History — Access full chat histories and event logs to understand customer context securely
- Operator Oversight — Monitor agent availability and list all operators in your account in real-time
- Status Management — Identify which agents are currently online to manage support load flawlessly
- Agent Insights — Retrieve your own operator profile and account metadata directly within your workspace
The Chaport MCP Server exposes 8 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 Chaport to LlamaIndex via MCP
Follow these steps to integrate the Chaport 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 8 tools from Chaport
Why Use LlamaIndex with the Chaport MCP Server
LlamaIndex provides unique advantages when paired with Chaport through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Chaport tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Chaport tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Chaport, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Chaport tools were called, what data was returned, and how it influenced the final answer
Chaport + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Chaport MCP Server delivers measurable value.
Hybrid search: combine Chaport real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Chaport 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 Chaport for fresh data
Analytical workflows: chain Chaport queries with LlamaIndex's data connectors to build multi-source analytical reports
Chaport MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Chaport to LlamaIndex via MCP:
get_chat_history
Retrieve the message history and events for a specific chat
get_my_agent_profile
Retrieve information about the authenticated agent
get_visitor_details
Get detailed information for a specific visitor
get_visitor_last_chat
Retrieve the last chat session for a specific visitor
list_chaport_operators
List all operators in your Chaport account
list_online_agents
List all agents who are currently online
list_website_visitors
List recent visitors to your website
send_agent_message
Send a message to a visitor in a specific chat
Example Prompts for Chaport in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Chaport immediately.
"List all website visitors from the last hour."
"Which support agents are currently online in Chaport?"
"Show me the message history for chat ID 123456."
Troubleshooting Chaport MCP Server with LlamaIndex
Common issues when connecting Chaport to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpChaport + LlamaIndex FAQ
Common questions about integrating Chaport 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 Chaport 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 Chaport to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.