2Chat MCP Server for LlamaIndex 5 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add 2Chat 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 2Chat. "
"You have 5 tools available."
),
)
response = await agent.run(
"What tools are available in 2Chat?"
)
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 2Chat MCP Server
Unlock the full potential of WhatsApp automation with 2Chat, the programmable gateway now integrated with your AI agent. By connecting 2Chat via the Model Context Protocol, you transcend the limitations of traditional messaging apps. Your agent can now orchestrate complex group workflows, verify phone numbers before sending, and manage multi-device communications through simple natural language. Whether you're coordinating team alerts or engaging with a community, 2Chat gives your AI the 'voice' it needs on the world's most popular messaging platform.
LlamaIndex agents combine 2Chat tool responses with indexed documents for comprehensive, grounded answers. Connect 5 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
- Programmable Messaging — Send text, images, PDF, and voice messages to any WhatsApp number without template restrictions.
- Group Management — Create groups, add participants, and send group-wide announcements directly from your chat interface.
- Number Verification — Check if a phone number is registered on WhatsApp before sending to improve delivery success.
- Webhooks & Real-time — Monitor incoming messages and delivery status (sent, delivered, read) seamlessly.
- Multi-Device Support — Link multiple WhatsApp numbers to a single API workspace for unified communications.
The 2Chat MCP Server exposes 5 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 2Chat to LlamaIndex via MCP
Follow these steps to integrate the 2Chat 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 5 tools from 2Chat
Why Use LlamaIndex with the 2Chat MCP Server
LlamaIndex provides unique advantages when paired with 2Chat through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine 2Chat tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain 2Chat tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query 2Chat, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what 2Chat tools were called, what data was returned, and how it influenced the final answer
2Chat + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the 2Chat MCP Server delivers measurable value.
Hybrid search: combine 2Chat real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query 2Chat 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 2Chat for fresh data
Analytical workflows: chain 2Chat queries with LlamaIndex's data connectors to build multi-source analytical reports
2Chat MCP Tools for LlamaIndex (5)
These 5 tools become available when you connect 2Chat to LlamaIndex via MCP:
check_number
Helps prevent failed delivery errors. Verify if a phone number is registered on WhatsApp
create_group
Create a new WhatsApp group with specified participants
list_groups
List all WhatsApp groups that a connected number belongs to
list_numbers
Use this to identify which "from_number" to use in subsequent sending actions. List all WhatsApp phone numbers connected to your 2Chat account
send_message
Can send text or public URL media to direct numbers or a specific group UUID. Send a WhatsApp text or media message using a connected number
Example Prompts for 2Chat in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with 2Chat immediately.
"Check if +123456789 is registered on WhatsApp and send a message saying hello."
"List all my WhatsApp groups."
"Create a new WhatsApp group called 'Project Gamma' and add participant +198765432."
Troubleshooting 2Chat MCP Server with LlamaIndex
Common issues when connecting 2Chat to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcp2Chat + LlamaIndex FAQ
Common questions about integrating 2Chat 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 2Chat 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 2Chat to LlamaIndex
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.