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 LlamaIndex 12 tools — connect in under 2 minutes

Name: Front
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Front as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Front. "
            "You have 12 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Front?"
    )
    print(response)

asyncio.run(main())

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* 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.

LlamaIndex agents combine Front tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Front MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 12 tools from Front

Why Use LlamaIndex with the Front MCP Server

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

Data-first architecture: LlamaIndex agents combine Front tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Front tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Front, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Front tools were called, what data was returned, and how it influenced the final answer

Front + LlamaIndex Use Cases

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

Hybrid search: combine Front real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Front to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Front for fresh data

Analytical workflows: chain Front queries with LlamaIndex's data connectors to build multi-source analytical reports

Front MCP Tools for LlamaIndex (12)

These 12 tools become available when you connect Front to LlamaIndex 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 LlamaIndex

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

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Front + LlamaIndex FAQ

Common questions about integrating Front MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.