How to Use the Bland AI MCP in LlamaIndex

Q: Is it easy to filter Bland AI tools in LlamaIndex?

You can use the allowedtools filter when defining your agent. This limits the scope of what your agent can access during a query.

Index your Bland AI call data into LlamaIndex to build searchable knowledge bases from voice interactions.

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Connect Bland AI MCP to LlamaIndex

Create your Vinkius account to connect Bland AI 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 Bland AI with LlamaIndex

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Query Bland AI calls with LlamaIndex

Index the output of `get_call_details` into your vector store. You can search across historical transcripts to find patterns in customer feedback. This makes your past phone conversations a searchable knowledge base. Your agents ground their answers in actual customer voice data.

Automate voice agent discovery in LlamaIndex

Run `list_voice_agents` to pull your current configuration into your index. This helps your RAG pipeline understand which personas are currently active. Your application stays aware of every deployed agent. You can build tools that query specific agent settings using `get_agent_config`.

Manage phone inventory for LlamaIndex apps

Use `list_phone_numbers` to track your available lines. You can feed this list into your agent's decision logic to select the right caller ID. It keeps your phone inventory synced with your application logic. You never have to update your code manually when you add new numbers.

Setup guide

Set up Bland AI 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 Bland AI 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 Bland AI tools.",
)
response = await agent.run("List recent Bland AI 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 Bland AI. 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

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Common questions about Bland AI MCP in LlamaIndex

Use the server tools to fetch call data and pass it into your indexing pipeline. Once indexed, your vector store handles the semantic search queries.

It does. You treat the server output as a data source. This allows your agent to answer questions based on the content of recent calls.

Yes. You can fetch agent settings and store them as metadata. This allows your app to reason about agent behavior based on stored configuration data.

You can use the allowed_tools filter when defining your agent. This limits the scope of what your agent can access during a query.

We enforce strict transport security for all transcript data. Your recordings are only accessible through the authenticated MCP connection you manage.

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