How to Use the Nimbata MCP in LlamaIndex

Q: How do I connect the Nimbata MCP Server to LlamaIndex?

Use pip install llama-index-tools-mcp to install the package. Initialize the BasicMCPClient with your Vinkius URL, convert it to a tool spec, and pass it to your agent.

Q: Can LlamaIndex query historical Nimbata call records?

Yes. Your agent can call searchcalls to fetch past call records, then index those results for semantic retrieval.

Q: How does LlamaIndex handle tool filtering with Nimbata?

You can use the allowedtools filter when defining your McpToolSpec to restrict your agent to specific tools like listnumbers.

Q: Can I retrieve specific tracking source configurations?

Yes, the agent can invoke getsource to fetch configuration details for any specific marketing channel.

Q: Where do my customer phone numbers and call metadata go?

All customer phone numbers and metadata pulled via listcalls are processed inside Vinkius's isolated V8 sandboxes. Your raw data is never stored by the server, keeping your customer identities safe.

Index live call tracking data from the Nimbata MCP Server directly into your LlamaIndex vector store for semantic search.

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Connect Nimbata MCP to LlamaIndex

Create your Vinkius account to connect Nimbata 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.

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Setup Nimbata with LlamaIndex

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Turn Phone Calls into Searchable LlamaIndex RAG Data

Stop letting valuable phone conversations sit dead in your call logs. This MCP Server setup lets your agent search call transcripts and metadata semantically. By using `get_call_details` and `get_call_recording`, you can pull live interaction data and index it directly into your vector database. This means you can ask your agent questions about what customers are saying on the phone. It queries the index and returns answers grounded in real call data, bypassing the hallucination issues of raw LLM queries.

Ground LlamaIndex Queries in Nimbata MCP Server Reports

Your agent can query live marketing reports to answer business questions. By mapping the `get_source_report` and `get_call_report` tools, the agent pulls fresh performance metrics on demand. The agent combines this live API data with your static marketing documents. You get a unified, queryable view of your campaign performance without manually exporting CSV files.

Dynamically Map Call Sources to Knowledge Bases

Keep your marketing knowledge base updated in real time. Your agent can run `list_sources` to check active tracking setups and index the results. When you launch a new ad campaign, the agent automatically detects it. It links the new source details from `get_source` to your existing campaign documentation inside your index.

Setup guide

Set up Nimbata 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 Nimbata 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 Nimbata tools.",
)
response = await agent.run("List recent Nimbata data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Nimbata. 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.

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Common questions about Nimbata MCP in LlamaIndex

Use `pip install llama-index-tools-mcp` to install the package. Initialize the `BasicMCPClient` with your Vinkius URL, convert it to a tool spec, and pass it to your agent.

Yes. Your agent can call `search_calls` to fetch past call records, then index those results for semantic retrieval.

You can use the `allowed_tools` filter when defining your `McpToolSpec` to restrict your agent to specific tools like `list_numbers`.

Yes, the agent can invoke `get_source` to fetch configuration details for any specific marketing channel.

All customer phone numbers and metadata pulled via `list_calls` are processed inside Vinkius's isolated V8 sandboxes. Your raw data is never stored by the server, keeping your customer identities safe.

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