CallFire MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Get Call, Get Campaign, Get Contact, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add CallFire 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 CallFire app connector for LlamaIndex is a standout in the Communication Messaging category — giving your AI agent 10 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 CallFire. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in CallFire?"
)
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 CallFire MCP Server
Connect your CallFire account to any AI agent and manage your voice and SMS communication workflows through natural conversation.
LlamaIndex agents combine CallFire 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
- Contact Management — List all contacts and retrieve individual contact profiles with phone numbers and metadata
- Call Tracking — Browse all inbound and outbound calls with duration, status, and call recording details
- SMS History — Review sent and received text messages with delivery status and timestamps
- Campaign Monitoring — List all broadcast campaigns (voice and text) and inspect individual campaign configurations and performance
- Webhook Management — View all configured webhooks and inspect their delivery settings and event triggers
The CallFire 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.
All 10 CallFire tools available for LlamaIndex
When LlamaIndex connects to CallFire through Vinkius, your AI agent gets direct access to every tool listed below — spanning sms-marketing, voice-broadcast, call-tracking, 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.
Get a specific call
Get a specific broadcast campaign
Get a specific contact
Get a specific text message
Get a specific webhook
List all calls
List all broadcast campaigns
List all contacts
List all text messages
List all webhooks
Connect CallFire to LlamaIndex via MCP
Follow these steps to wire CallFire 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 CallFire MCP Server
LlamaIndex provides unique advantages when paired with CallFire through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine CallFire tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain CallFire tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query CallFire, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what CallFire tools were called, what data was returned, and how it influenced the final answer
CallFire + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the CallFire MCP Server delivers measurable value.
Hybrid search: combine CallFire real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query CallFire 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 CallFire for fresh data
Analytical workflows: chain CallFire queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for CallFire in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with CallFire immediately.
"Show me all active broadcast campaigns and their delivery rates."
"List all text messages sent in the last 24 hours and highlight any that failed delivery."
"How many contacts do I have and are there any with missing phone numbers?"
Troubleshooting CallFire MCP Server with LlamaIndex
Common issues when connecting CallFire to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCallFire + LlamaIndex FAQ
Common questions about integrating CallFire MCP Server with LlamaIndex.