NeonCRM MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect NeonCRM through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"neoncrm": {
"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 NeonCRM, 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 NeonCRM MCP Server
Connect your NeonCRM account to your AI agent and take full control of your non-profit organization's constituent data and fundraising activities through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with NeonCRM through native MCP adapters. Connect 10 tools via the 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.
What you can do
- Constituent Management — List all accounts and contacts to get detailed profiles and historical activity.
- Donation Tracking — Access a history of all financial contributions and retrieve metadata for specific donations.
- Membership Oversight — Monitor active and historical membership records for your supporters.
- Event Management — View all organization events (fundraisers, galas) and registration details.
- Grant Tracking — List and inspect grant applications and awards managed within the CRM.
- Custom Data Access — Retrieve all standard and custom data fields defined for your CRM profiles.
The NeonCRM 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 NeonCRM to LangChain via MCP
Follow these steps to integrate the NeonCRM 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 NeonCRM via MCP
Why Use LangChain with the NeonCRM MCP Server
LangChain provides unique advantages when paired with NeonCRM through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine NeonCRM 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 NeonCRM queries for multi-turn workflows
NeonCRM + LangChain Use Cases
Practical scenarios where LangChain combined with the NeonCRM MCP Server delivers measurable value.
RAG with live data: combine NeonCRM tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query NeonCRM, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain NeonCRM tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every NeonCRM tool call, measure latency, and optimize your agent's performance
NeonCRM MCP Tools for LangChain (10)
These 10 tools become available when you connect NeonCRM to LangChain via MCP:
get_account
Get specific account details
get_crm_event
Get specific event details
get_donation
Get donation details
list_accounts
List NeonCRM accounts
list_contacts
List CRM contacts
list_crm_events
) created in NeonCRM. List CRM events
list_custom_fields
List CRM custom fields
list_donations
List all donations
list_grants
List grant records
list_memberships
List account memberships
Example Prompts for NeonCRM in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with NeonCRM immediately.
"List all donations received this year."
"Show me the details for account ID 987."
"List all upcoming CRM events."
Troubleshooting NeonCRM MCP Server with LangChain
Common issues when connecting NeonCRM to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersNeonCRM + LangChain FAQ
Common questions about integrating NeonCRM 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 NeonCRM 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 NeonCRM to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.