How to Use the Bloom Credit MCP in LlamaIndex

Index your credit reports into LlamaIndex. Turn raw consumer data into a searchable knowledge base for your AI.

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Connect Bloom Credit MCP to LlamaIndex

Create your Vinkius account to connect Bloom Credit 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 Bloom Credit with LlamaIndex

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Build a searchable index with Bloom Credit

Turn your credit report results into vector embeddings. Use `get_report_data` to pull the raw info, then let LlamaIndex store it for semantic retrieval. Your agent can now answer questions about consumer credit history by querying the index. It stops hallucinating because it works from the actual data retrieved by the server.

Query past credit orders in LlamaIndex

Maintain a persistent history of every credit pull. By calling `list_orders` and indexing the output, you create a searchable archive of your consumer interactions. This allows your LlamaIndex application to reference past reports instantly. You don't need to re-query the API when you have the data indexed and ready for retrieval.

Retrieve specific consumer records

Grab details for a specific individual using `get_consumer`. Once your agent finds the ID, it can pull the full report and add it to your current context window. This makes building RAG applications for finance tasks much faster. You feed the output of these tools directly into your index to ground every response.

Setup guide

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

Use the llama-index-tools-mcp package to wrap the Bloom Credit server. Once wrapped, your FunctionAgent can use the tools to pull data for your index.

No, because the tool outputs are indexed directly into your vector store. Your agent answers based on the ground truth retrieved from the API.

The data is handled within your secure Vinkius environment. You decide which reports get indexed and who can query that store.

You can mix live tool calls with your indexed data. Use the tools to fetch fresh reports and let the index provide context from historical records.

It resides in your chosen vector store. Vinkius ensures the transport between the credit API and your client remains encrypted and ephemeral.

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