How to Use the Double the Donation MCP in LlamaIndex

Q: Can I query Double the Donation match rules in LlamaIndex using semantic search?

Yes. By indexing the outputs of searchcompany and getcompany into LlamaIndex, you can search for match criteria using natural language. This lets your agent find matching policies even when the donor uses non-standard company names.

Q: How does LlamaIndex prevent hallucinations when calling Double the Donation tools?

LlamaIndex uses the live outputs from getdonation and getdashboardstats to ground its responses. The agent is forced to use the actual data returned by these tools rather than relying on its pre-trained weights, keeping match details accurate.

Q: What tools should I expose to my LlamaIndex query agent?

You should expose searchcompany, getcompany, and listdonations to give your agent full context. This allows it to find the donor's employer, verify the matching guidelines, and check the status of existing match requests in one session.

Q: How does this setup protect our organization settings?

All configuration data handled by getaccountsettings and updateorganization is processed in memory within Vinkius's secure, ephemeral V8 isolates. The server never writes your API credentials or organization settings to disk, keeping your administrative data isolated.

Index employer matching rules into your LlamaIndex vector store using the Double the Donation MCP Server.

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Connect Double the Donation MCP to LlamaIndex

Create your Vinkius account to connect Double the Donation 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 Double the Donation with LlamaIndex

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Index matching gift data for LlamaIndex RAG

Your LlamaIndex pipeline uses `get_company` to pull live match policies and stop letting data sit idle in isolated silos. This MCP Server lets your LlamaIndex pipeline pull live match policies and index them directly into your vector database. Instead of hardcoded lookups, you query your index to find which companies match donations for part-time employees or retirees. The engine uses `list_subsidiaries` to map parent-child corporate relationships, storing the entire hierarchy as searchable document nodes in your index.

Ground agent responses in real-time donor stats

The `get_donation` tool ensures your agent never hallucinates matching gift details and loses donor trust. By integrating this server with LlamaIndex, your query engine fetches live data using `get_dashboard_stats` and `get_donation` before generating any response. When a donor asks about their match status, the LlamaIndex agent pulls the exact record with `get_donation`. It combines this live API data with your indexed knowledge base, ensuring the final answer is perfectly accurate and grounded in real-time records.

Automate account onboarding and lookups

You use `create_organization` to provision new 360MatchPro accounts directly through conversational commands. Setting up new corporate matching profiles shouldn't require manual database scripts. Once provisioned, the agent can immediately run `get_account_settings` to verify the setup. This allows you to build self-configuring ingestion pipelines that prepare the environment, run matching lookups via `search_company`, and index the results without manual intervention.

Setup guide

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

You use the MCP client to connect to the server, then wrap it in `McpToolSpec` to extract the tools. Your pipeline can call `get_company` or `list_subsidiaries` to fetch matching policies, which you then parse into Document objects and insert into your vector index.

Yes. By indexing the outputs of `search_company` and `get_company` into LlamaIndex, you can search for match criteria using natural language. This lets your agent find matching policies even when the donor uses non-standard company names.

LlamaIndex uses the live outputs from `get_donation` and `get_dashboard_stats` to ground its responses. The agent is forced to use the actual data returned by these tools rather than relying on its pre-trained weights, keeping match details accurate.

You should expose `search_company`, `get_company`, and `list_donations` to give your agent full context. This allows it to find the donor's employer, verify the matching guidelines, and check the status of existing match requests in one session.

All configuration data handled by `get_account_settings` and `update_organization` is processed in memory within Vinkius's secure, ephemeral V8 isolates. The server never writes your API credentials or organization settings to disk, keeping your administrative data isolated.

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