How do I get an API Token for Front?

Log in to your Front account, click the gear icon (Settings), go to 'Developers' > 'API Tokens', and create a new token with 'Shared Resources' scope.

Can I search for specific types of conversations?

Yes, use the 'search_conversations' tool. It accepts standard Front search syntax, such as 'is:open' or 'inbox:support'.

Is it possible to reply to an email via the agent?

Yes! Use the 'send_inbox_reply' tool. You must provide the Conversation ID, the message body, and the Teammate ID of the sender.

How do I archive a conversation?

Use the 'update_conversation_status' tool and set the status parameter to 'archived'. This updates the global status for the shared inbox.

Front MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Front
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Front through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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({
        "front": {
            "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 Front, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 Front MCP Server

Connect your Front account to any AI agent to automate your customer communication and shared inbox workflows through the Model Context Protocol (MCP). Front is a customer operations platform that enables teams to manage shared emails, SMS, and chats collaboratively. This MCP server enables you to track active conversations, assign messages, and fetch thread histories directly through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Front 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.

Key Features

Shared Inbox Management — List all accessible shared inboxes and retrieve the specific conversations routed to them.
Conversation Tracking — Search and list all customer conversations, checking their current status (open, archived) and assigned owners.
Message Threading — Fetch the complete message history for any specific conversation to maintain context before replying.
Collaborative Replies — Draft and send replies to active conversations directly from your chat interface on behalf of a teammate.
Status Automation — Programmatically update conversation statuses (e.g., archiving resolved issues) to keep inboxes clean.
Team & Contact Discovery — List all workspace teammates and customer contacts to ensure accurate routing and messaging.

The Front 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.

How to Connect Front to LangChain via MCP

Follow these steps to integrate the Front 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 12 tools from Front via MCP

Why Use LangChain with the Front MCP Server

LangChain provides unique advantages when paired with Front through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Front 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 Front queries for multi-turn workflows

Front + LangChain Use Cases

Practical scenarios where LangChain combined with the Front MCP Server delivers measurable value.

RAG with live data: combine Front tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Front, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Front tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Front tool call, measure latency, and optimize your agent's performance

Front MCP Tools for LangChain (12)

These 12 tools become available when you connect Front to LangChain via MCP:

get_conversation_details

Get conversation metadata

get_inbox_details

Get inbox metadata

list_address_book

List contacts

list_all_conversations

List all conversations

list_conversation_messages

List thread messages

list_inbox_teammates

List Front teammates

list_inbox_threads

List inbox conversations

list_shared_inboxes

List shared inboxes

search_conversations

g. "inbox:inb_123 is:open"). Search all conversations

send_inbox_reply

Send a reply

update_conversation_status

g., archived, open) or assignee of a conversation. Update conversation

verify_api_status

Verify connection

Example Prompts for Front in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Front immediately.

"List all shared inboxes in my Front account."

"Search for open conversations in the Support inbox."

"Archive conversation 'cnv_987'."

Troubleshooting Front MCP Server with LangChain

Common issues when connecting Front to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Front + LangChain FAQ

Common questions about integrating Front MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.