SignalWire 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 SignalWire 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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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 SignalWire. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in SignalWire?"
)
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 SignalWire MCP Server
Empower your AI agent to orchestrate your entire cloud communication infrastructure with SignalWire, the advanced platform for messaging, voice, and video. By connecting SignalWire to your agent, you transform complex telecom management into a natural conversation. Your agent can instantly list your phone numbers, audit message delivery, and retrieve call logs without you ever touching a technical console. Whether you are providing customer alerts or managing corporate voice lines, your agent acts as a real-time telecom operator, ensuring your communication is always reliable and your usage data is organized.
LlamaIndex agents combine SignalWire 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
- Messaging Intelligence — Send SMS messages instantly and retrieve detailed message status and history.
- Call Auditing — List all recent voice calls and retrieve metadata for each, including direction and duration.
- Number Oversight — List and monitor all incoming phone numbers associated with your project.
- Usage Intelligence — Retrieve detailed usage records to maintain strict organizational control over your communication costs.
- Account Governance — Monitor account-wide metadata to understand your project status in real-time.
The SignalWire 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 SignalWire to LlamaIndex via MCP
Follow these steps to integrate the SignalWire 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 SignalWire
Why Use LlamaIndex with the SignalWire MCP Server
LlamaIndex provides unique advantages when paired with SignalWire through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SignalWire tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SignalWire tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SignalWire, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SignalWire tools were called, what data was returned, and how it influenced the final answer
SignalWire + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SignalWire MCP Server delivers measurable value.
Hybrid search: combine SignalWire real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SignalWire 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 SignalWire for fresh data
Analytical workflows: chain SignalWire queries with LlamaIndex's data connectors to build multi-source analytical reports
SignalWire MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect SignalWire to LlamaIndex via MCP:
get_account_info
Get SignalWire account details
get_call
Get details for a specific call
get_message
Get details for a specific message
list_calls
List recent voice calls
list_messages
List recent SMS/MMS messages
list_phone_numbers
List SignalWire phone numbers
list_usage
Get account usage records
send_sms
Send an SMS message
Example Prompts for SignalWire in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with SignalWire immediately.
"List all my SignalWire phone numbers."
"Send SMS 'Server alert: high usage detected' to +15550123."
"Show me recent call logs for my project."
Troubleshooting SignalWire MCP Server with LlamaIndex
Common issues when connecting SignalWire to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSignalWire + LlamaIndex FAQ
Common questions about integrating SignalWire 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 SignalWire 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 SignalWire to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.