How to Use the FundraisingBox MCP in LlamaIndex

Q: Does this FundraisingBox server support filtering?

Yes. You can use the allowedtools filter in your client setup to restrict which parts of the API your index can access.

Index live donor data into LlamaIndex to build RAG applications that answer questions using your actual FundraisingBox records.

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Connect FundraisingBox MCP to LlamaIndex

Create your Vinkius account to connect FundraisingBox 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 FundraisingBox with LlamaIndex

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Vectorize FundraisingBox in LlamaIndex

Pull data using `list_donors` and convert it into a searchable knowledge base. Your LlamaIndex application indexes these profiles for instant retrieval. This approach grounds your AI responses in real facts. Instead of guessing, your agent searches your specific donor database.

Query donation receipts via MCP

The `list_receipts` tool brings raw financial records into your index. You can ask questions about specific payment dates or donor contributions. LlamaIndex treats these outputs as queryable documents. It combines your API data with your local files for a unified search experience.

Analyze campaigns using MCP Server tools

Fetch campaign details with `get_campaign` and `list_campaigns`. These tools provide the raw content for your vector store. Your application gains a deep understanding of your fundraising efforts. You get answers based on the latest data directly from the platform.

Setup guide

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

You use the llama-index-tools-mcp package to define the tool spec. This client allows your agent to perform search operations on live data.

Absolutely. Once the tools are indexed, you can run semantic queries to find donor profiles matching specific criteria.

Yes. You can use the allowed_tools filter in your client setup to restrict which parts of the API your index can access.

Trigger your LlamaIndex pipeline to re-fetch data using the tools. It updates the vector store with the most recent API results.

Your donor records are encrypted in transit via the MCP protocol. No data is cached by the server after the request finishes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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