How to Use the Donorbox MCP in LlamaIndex

Index your Donorbox fundraising history into LlamaIndex for semantic search and grounded donor insights.

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Connect Donorbox MCP to LlamaIndex

Create your Vinkius account to connect Donorbox 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 Donorbox with LlamaIndex

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Semantic search for Donorbox in LlamaIndex

Convert your donation logs into a searchable vector index. `list_donorbox_donations` provides the raw data that LlamaIndex turns into a queryable knowledge base. You ask natural language questions about your fundraising history. The system retrieves specific contribution details based on the context of your query rather than exact keyword matches.

Grounded campaign analysis

Index your `get_campaign_details` output to provide your agent with permanent context. This prevents hallucinations by forcing the agent to rely on your actual campaign settings. Your agent builds a summary based on the indexed data. It checks the performance audit tools to ensure its responses match your live account status.

Unified donor knowledge base

Combine `list_registered_donors` with your internal documentation. LlamaIndex merges these data sources into a single index for deep donor research. You find donor history faster by searching across both API data and external notes. The agent retrieves contact details and donation frequency in one go.

Setup guide

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

It turns static donation records into a searchable index. This is better for finding patterns in years of historical data.

Absolutely, just pass the tools to your agent. It will fetch the latest stats and index them for your current session.

Your donor data is stored locally in your vector index. You control the access and the lifecycle of this information entirely.

Trigger a re-index after running your tools. This ensures your agent always works with the most recent contribution data.

It stores donor names, email addresses, and contribution histories. All data is handled as standard text strings within your private vector storage.

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

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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