How to Use the Goodcall MCP in LlamaIndex

Build a searchable knowledge base of your calls in LlamaIndex to query history and booking patterns instantly.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Goodcall MCP to LlamaIndex

Create your Vinkius account to connect Goodcall to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Goodcall with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index your receptionist data with LlamaIndex

Convert your call history into a vector store for semantic search. When you run `list_calls`, the output is ready to be indexed so you can ask questions about past customer inquiries. Stop guessing what customers want. You can query your own history to find trends that don't show up in standard reports.

Grounded answers from live call transcripts

Retrieve exact details from past interactions using `get_transcript`. LlamaIndex uses these documents to ensure your AI answers are based on reality, not hallucinations. Your agent gets the context it needs to sound human. It looks up the latest conversation before it speaks, keeping the information accurate and relevant.

Manage bookings via vector-augmented search

Use the `list_bookings` tool to pull appointment data into your index. This allows your agent to compare current requests against existing schedules with high precision. It makes scheduling smarter. By combining live API data with your stored knowledge, the agent avoids conflicts and double bookings automatically.

Setup guide

Set up Goodcall MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Goodcall MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Goodcall tools.",
)
response = await agent.run("List recent Goodcall data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Goodcall. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Goodcall now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Goodcall MCP in LlamaIndex

The MCP tools fetch raw data from your account. LlamaIndex then parses these results into nodes that you can index for RAG workflows.

The tool outputs are formatted for easy ingestion. You simply map the output of `get_call_summary` to your document ingestion pipeline.

Your records are only accessed when the tools are invoked. The server ensures that only the specific call transcripts requested enter your local index.

Use the tool parameters to narrow down your request before indexing. You can target specific agents or date ranges to keep your vector store focused.

Yes, all data transit is encrypted. Only the authorized agent can pull the call details and store them in your secure index.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python