Hiver MCP Server for LangChainGive LangChain instant access to 12 tools to Create Shared Draft, Get Api Status, Get Conversation Details, and more
LangChain is the leading Python framework for composable LLM applications. Connect Hiver 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 App Connector for LangChain
The Hiver app connector for LangChain is a standout in the Communication Messaging category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"hiver": {
"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 Hiver, 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 Hiver MCP Server
Connect your Hiver account to any AI agent and transform your Gmail-based customer support into an intelligent, automated operation through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Hiver through native MCP adapters. Connect 12 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
- Shared Inbox Management — List all shared mailboxes and retrieve detailed metadata for active email conversations
- Workflow Automation — Programmatically update conversation statuses (open, pending, closed) and manage assignments across your team
- Collaborative Drafting — Create shared drafts within Gmail threads directly through your agent to orchestrate perfect replies
- Tagging & Organization — Search and apply tags to categorize threads and maintain a high-fidelity collaboration ecosystem
- Team Visibility — List and search for inbox members to understand who is available and manage workload distribution
The Hiver MCP Server exposes 12 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.
All 12 Hiver tools available for LangChain
When LangChain connects to Hiver through Vinkius, your AI agent gets direct access to every tool listed below — spanning shared-inbox, gmail-integration, email-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Draft team reply
Check connection
Read email thread
Get mailbox info
List shared threads
List team members
Get mailbox tags
List Hiver inboxes
Find tags
Find members
Verify credentials
Modify conversation
Connect Hiver to LangChain via MCP
Follow these steps to wire Hiver into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the Hiver MCP Server
LangChain provides unique advantages when paired with Hiver through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Hiver 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 Hiver queries for multi-turn workflows
Hiver + LangChain Use Cases
Practical scenarios where LangChain combined with the Hiver MCP Server delivers measurable value.
RAG with live data: combine Hiver tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Hiver, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Hiver tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Hiver tool call, measure latency, and optimize your agent's performance
Example Prompts for Hiver in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Hiver immediately.
"List all shared inboxes in my Hiver account."
"Show me the last 5 open conversations in the 'Support' inbox."
"Assign conversation 'thread-123' to user 'user-456' and add the tag 'priority'."
Troubleshooting Hiver MCP Server with LangChain
Common issues when connecting Hiver to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersHiver + LangChain FAQ
Common questions about integrating Hiver 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.