DonorsChoose MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect DonorsChoose 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({
"donorschoose": {
"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 DonorsChoose, 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 DonorsChoose MCP Server
Integrate DonorsChoose, the leading crowdfunding platform for public school teachers, directly into your AI workflow. Search for classroom projects across the US, filter by state, subject, or ZIP code, monitor urgent funding needs, and retrieve detailed information for educational proposals using natural language.
LangChain's ecosystem of 500+ components combines seamlessly with DonorsChoose 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.
What you can do
- Project Discovery — Search for classroom projects using keywords, subjects, or specific geographic locations (states and ZIP codes).
- Funding Oversight — Monitor projects that are close to their expiration or have high urgency to identify immediate support needs.
- Proposal Intelligence — Retrieve detailed information for specific classroom projects, including school details and itemized resource lists.
- Newest Opportunity Tracking — List the most recently posted classroom proposals to identify new funding opportunities across the organization.
The DonorsChoose 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 DonorsChoose to LangChain via MCP
Follow these steps to integrate the DonorsChoose 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 DonorsChoose via MCP
Why Use LangChain with the DonorsChoose MCP Server
LangChain provides unique advantages when paired with DonorsChoose through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine DonorsChoose 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 DonorsChoose queries for multi-turn workflows
DonorsChoose + LangChain Use Cases
Practical scenarios where LangChain combined with the DonorsChoose MCP Server delivers measurable value.
RAG with live data: combine DonorsChoose tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query DonorsChoose, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain DonorsChoose tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every DonorsChoose tool call, measure latency, and optimize your agent's performance
DonorsChoose MCP Tools for LangChain (10)
These 10 tools become available when you connect DonorsChoose to LangChain via MCP:
get_classroom_project_details
Get detailed information for a specific classroom project
get_donorschoose_api_metadata
Retrieve metadata for the current API connection
list_high_poverty_needs
Identify projects from schools in high-poverty areas
list_latest_classroom_proposals
List the most recently posted classroom projects
list_projects_by_state
List classroom projects in a specific US state (e.g., NY, CA)
list_projects_by_subject
List projects filtered by subject area (e.g., Literacy, Math)
list_urgent_funding_needs
Identify projects that are close to their expiration or have high urgency
quick_regional_funding_audit
Retrieve a high-level summary of active projects in a region
search_classroom_projects
Search for DonorsChoose classroom projects using keywords
search_projects_by_zipcode
Search for classroom projects within a specific US ZIP code
Example Prompts for DonorsChoose in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with DonorsChoose immediately.
"Search for classroom projects in New York about 'Literacy'."
"Show me urgent projects near ZIP code '90210'."
"List the newest classroom proposals."
Troubleshooting DonorsChoose MCP Server with LangChain
Common issues when connecting DonorsChoose to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersDonorsChoose + LangChain FAQ
Common questions about integrating DonorsChoose 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 DonorsChoose 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 DonorsChoose to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.