Givebutter MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Givebutter as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 Givebutter. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Givebutter?"
)
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 Givebutter MCP Server
Connect your Givebutter account to any AI agent to automate your fundraising operations and donor management through the Model Context Protocol (MCP). Givebutter is the modern fundraising platform for nonprofits and changemakers. This MCP server enables you to retrieve donation transactions, manage fundraising campaigns, and synchronize donor profiles (contacts) directly through natural conversation.
LlamaIndex agents combine Givebutter tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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 transactions, fetch detailed metadata including status and timestamps, and monitor your revenue flow instantly.
- Campaign Management — Access active fundraising campaigns and events, retrieving detailed configuration and total raised amounts.
- Donor Synchronization — Search and list donor profiles, retrieve detailed contact metadata, and programmatically add new donors to your database.
- Offline Recording — Record offline donations or external payments programmatically to maintain a unified source of truth for your fundraising.
- Recurring Plan Monitoring — List and track configured recurring donation plans to understand long-term donor commitment.
- Webhook Visibility — Monitor active webhooks to ensure your internal systems are receiving real-time donation notifications.
- Real-time Synchronization — Keep your nonprofit's financial data accessible to your AI assistant without leaving your primary workspace.
The Givebutter MCP Server exposes 12 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 Givebutter to LlamaIndex via MCP
Follow these steps to integrate the Givebutter 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 12 tools from Givebutter
Why Use LlamaIndex with the Givebutter MCP Server
LlamaIndex provides unique advantages when paired with Givebutter through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Givebutter tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Givebutter tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Givebutter, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Givebutter tools were called, what data was returned, and how it influenced the final answer
Givebutter + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Givebutter MCP Server delivers measurable value.
Hybrid search: combine Givebutter real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Givebutter 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 Givebutter for fresh data
Analytical workflows: chain Givebutter queries with LlamaIndex's data connectors to build multi-source analytical reports
Givebutter MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Givebutter to LlamaIndex via MCP:
get_account_details
Get account identity
get_campaign_details
Get campaign metadata
get_transaction_details
Get transaction metadata
list_donation_transactions
List donations
list_donation_webhooks
List webhook configs
list_donor_contacts
List donor profiles
list_fundraising_campaigns
List active campaigns
list_recent_donations
List last 10 success
list_recurring_plans
List recurring plans
record_offline_donation
Log a donation
sync_donor_contact
Add new donor
verify_api_connection
Check connection
Example Prompts for Givebutter in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Givebutter immediately.
"List all successful donations from the last 24 hours."
"Check the progress of our 'Annual Gala' campaign (ID: gala_2024)."
"Log an offline donation of $50.00 from 'Alice Smith' (ID: contact_123)."
Troubleshooting Givebutter MCP Server with LlamaIndex
Common issues when connecting Givebutter to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGivebutter + LlamaIndex FAQ
Common questions about integrating Givebutter 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 Givebutter 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 Givebutter to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.