How do I get an API Key for Givebutter?

Log in to your Givebutter dashboard, navigate to Settings > Developers > API, and you can generate a new secret API key there.

Can I process live credit card transactions via the agent?

No, this integration is for management and data retrieval. For security, live donor checkouts must still happen through Givebutter's secure forms.

What format should the donation amount be in?

The Givebutter API uses major units for amounts. For example, to record a $10.50 donation, you should provide the decimal value '10.50'.

How do I link a transaction to a specific campaign?

Use the 'campaign_id' parameter in the 'record_offline_donation' tool. You can find your campaign IDs using the 'list_fundraising_campaigns' tool.

Givebutter MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Givebutter
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Givebutter through Vinkius, pass the Edge URL in the `mcps` parameter and every Givebutter tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Givebutter Specialist",
    goal="Help users interact with Givebutter effectively",
    backstory=(
        "You are an expert at leveraging Givebutter tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Givebutter "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

When paired with CrewAI, Givebutter becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Givebutter tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Givebutter MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Givebutter

Why Use CrewAI with the Givebutter MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Givebutter through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Givebutter + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Givebutter MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Givebutter for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Givebutter, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Givebutter tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Givebutter against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Givebutter MCP Tools for CrewAI (12)

These 12 tools become available when you connect Givebutter to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Givebutter to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Givebutter + CrewAI FAQ

Common questions about integrating Givebutter MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.