How to Use the Braze MCP in LlamaIndex

Q: Can LlamaIndex query Braze campaign metrics directly?

Yes, your agent can call getcampaigndetails to fetch current campaign configurations. It then parses this raw JSON output to ground its answers in real marketing data.

Q: Does LlamaIndex support filtering which Braze tools are exposed?

Yes, you can use the allowedtools filter during the McpToolSpec initialization. This allows you to expose only read-only tools like listcanvases while blocking trigger tools.

Index Braze campaign data and trigger customer journeys from your LlamaIndex RAG pipeline.

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Connect Braze MCP to LlamaIndex

Create your Vinkius account to connect Braze 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 Braze with LlamaIndex

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Index your Braze campaigns for semantic search

The Braze MCP Server allows your LlamaIndex agent to pull live marketing data directly into your vector store. By calling `list_campaigns` and `get_campaign_details`, the agent indexes your current copy and settings to answer questions about active marketing efforts. This stops your system from hallucinating campaign details. Instead of relying on static docs, your RAG pipeline queries live API data to verify exactly what messaging is active.

Query and trigger Braze Canvas journeys via LlamaIndex

This MCP Server turns your marketing automation into queryable nodes inside your LlamaIndex index. An agent can search your onboarding setups using `list_canvases` and trigger a specific path with `trigger_canvas` based on user query context. You load these tools using the McpToolSpec class. The framework converts the tool outputs into structured documents, making them immediately available for downstream synthesis steps.

Sync user profiles based on semantic context

The Braze integration gives your indexing pipeline the ability to update customer profiles on the fly. Your agent uses `track_user` to log user attributes derived from chat transcripts or search history, keeping your marketing database accurate. You can also clean up or merge profiles during index maintenance. The agent runs `identify_user` or `delete_user` to keep your user records organized based on your data policy.

Setup guide

Set up Braze 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 Braze 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 Braze tools.",
)
response = await agent.run("List recent Braze 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 Braze. 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 Braze MCP in LlamaIndex

Use the llama-index-tools-mcp package to initialize the BasicMCPClient, which manages the MCP connection. Then, wrap it in McpToolSpec and call the to_tool_list_async method to get tools ready for your FunctionAgent.

Yes, your agent can call `get_campaign_details` to fetch current campaign configurations. It then parses this raw JSON output to ground its answers in real marketing data.

Yes, you can use the allowed_tools filter during the McpToolSpec initialization. This allows you to expose only read-only tools like `list_canvases` while blocking trigger tools.

The server passes Braze API rate limit headers back to LlamaIndex. Your agent or orchestrator can catch these status codes and implement backoff strategies before retrying.

Yes. Vinkius operates a zero-trust architecture where all interactions with this MCP server occur within single-use, sandboxed containers. No raw payload data is cached, and your API credentials are encrypted at rest using industry-standard KMS envelopes.

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