GivingFuel MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect GivingFuel through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"givingfuel": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using GivingFuel, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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.
LangChain's ecosystem of 500+ components combines seamlessly with GivingFuel through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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 LangChain 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 LangChain via MCP
Follow these steps to integrate the GivingFuel MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from GivingFuel via MCP
Why Use LangChain with the GivingFuel MCP Server
LangChain provides unique advantages when paired with GivingFuel through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine GivingFuel MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across GivingFuel queries for multi-turn workflows
GivingFuel + LangChain Use Cases
Practical scenarios where LangChain combined with the GivingFuel MCP Server delivers measurable value.
RAG with live data: combine GivingFuel tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query GivingFuel, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain GivingFuel tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every GivingFuel tool call, measure latency, and optimize your agent's performance
GivingFuel MCP Tools for LangChain (10)
These 10 tools become available when you connect GivingFuel to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting GivingFuel to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGivingFuel + LangChain FAQ
Common questions about integrating GivingFuel MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
