ChatGen MCP Server for LlamaIndexGive LlamaIndex instant access to 9 tools to Create Bot, Delete Bot, Get Bot, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ChatGen 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 ChatGen app connector for LlamaIndex is a standout in the Customer Support category — giving your AI agent 9 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 ChatGen. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in ChatGen?"
)
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 ChatGen MCP Server
Connect your ChatGen account to any AI agent and simplify your conversational marketing and lead management through natural conversation.
LlamaIndex agents combine ChatGen tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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
- Bot Management — List all your chatbots, retrieve detailed configuration metadata, and create or update bots programmatically
- Lead Generation — Query and analyze leads captured by your bots to sync with your sales workflows
- Conversation Tracking — Monitor recent chat sessions to understand user interactions and bot performance
- Team Insights — List organizational teams to understand your account structure
The ChatGen MCP Server exposes 9 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 9 ChatGen tools available for LlamaIndex
When LlamaIndex connects to ChatGen through Vinkius, your AI agent gets direct access to every tool listed below — spanning conversational-marketing, lead-capture, chatbot, 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 chatbot
Delete a bot
Get details for a specific bot
Get details for a specific lead
List all ChatGen bots
List recent bot conversations
List captured leads
List organizational teams
Update an existing bot
Connect ChatGen to LlamaIndex via MCP
Follow these steps to wire ChatGen 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 ChatGen MCP Server
LlamaIndex provides unique advantages when paired with ChatGen through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine ChatGen tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain ChatGen tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query ChatGen, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what ChatGen tools were called, what data was returned, and how it influenced the final answer
ChatGen + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the ChatGen MCP Server delivers measurable value.
Hybrid search: combine ChatGen real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query ChatGen 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 ChatGen for fresh data
Analytical workflows: chain ChatGen queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for ChatGen in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with ChatGen immediately.
"List all my ChatGen bots."
"Show me details for the lead 'lead_999'."
"Find recent bot conversations."
Troubleshooting ChatGen MCP Server with LlamaIndex
Common issues when connecting ChatGen to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpChatGen + LlamaIndex FAQ
Common questions about integrating ChatGen MCP Server with LlamaIndex.