GivingFuel MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GivingFuel as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to GivingFuel. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in GivingFuel?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About GivingFuel MCP Server
Connect your GivingFuel account to any AI agent to automate your fundraising data extraction and donor relationship management through the Model Context Protocol (MCP). GivingFuel is a powerful, flexible fundraising platform for nonprofits and ministries. This MCP server enables you to retrieve donation orders, track individual donor responses (registrants), and monitor active fundraising pages directly through natural conversation.
LlamaIndex agents combine GivingFuel tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
Key Features
- Donation Oversight — List all donation orders for your organization, including transaction totals and status (completed, refunded, pending).
- Donor Detail Discovery — Retrieve detailed records for individual donors and their specific form responses to understand donor sentiment.
- Financial Transaction Tracking — Access financial processing data for both successful and failed charges to monitor payment health.
- Page Management — List all active fundraising pages and events, retrieving detailed configuration metadata for each.
- Donor CRM Insights — Access unified donor profiles from the Webconnex platform to track long-term donor engagement.
- P2P Campaign Discovery — Retrieve data related to Peer-to-Peer fundraising campaigns and participant activity.
- Real-time Synchronization — Keep your organization's fundraising data accessible to your AI assistant without leaving your primary workspace.
The GivingFuel MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect GivingFuel to LlamaIndex via MCP
Follow these steps to integrate the GivingFuel MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from GivingFuel
Why Use LlamaIndex with the GivingFuel MCP Server
LlamaIndex provides unique advantages when paired with GivingFuel through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GivingFuel tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GivingFuel tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GivingFuel, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GivingFuel tools were called, what data was returned, and how it influenced the final answer
GivingFuel + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GivingFuel MCP Server delivers measurable value.
Hybrid search: combine GivingFuel real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GivingFuel to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying GivingFuel for fresh data
Analytical workflows: chain GivingFuel queries with LlamaIndex's data connectors to build multi-source analytical reports
GivingFuel MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect GivingFuel to LlamaIndex via MCP:
filter_orders_by_date
Filter by date range
filter_orders_by_status
Filter by completion
list_crm_contacts
List donor profiles
list_donation_orders
List all orders
list_donation_registrants
List individual donors
list_financial_transactions
List successful charges
list_fundraising_pages
List donation pages
list_peer_campaigns
List P2P campaigns
list_recent_donations
List latest 10 orders
verify_api_connection
Check connection
Example Prompts for GivingFuel in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GivingFuel immediately.
"List the last 5 donation orders received."
"Show me all fundraising pages active in my account."
"How many donations were marked as 'refunded' today?"
Troubleshooting GivingFuel MCP Server with LlamaIndex
Common issues when connecting GivingFuel to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGivingFuel + LlamaIndex FAQ
Common questions about integrating GivingFuel MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect GivingFuel with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect GivingFuel to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.