How do I get my Intercom Access Token?

Go to the **Intercom Developer Hub** at **app.intercom.com/a/developer-hub/**. Click **New app**, give it a name, and select the workspace to install it in. Once created, click on your app, then navigate to **Authentication** in the left sidebar. Your **Access Token** will be displayed on this page. Configure the required permissions (scopes) — such as Read/Write People, Conversations, or Companies — and click **Save**. Copy the token and paste it below.

Can I look up a customer's full conversation history instantly?

Yes. Just ask your AI agent 'Show me all conversations with john@acme.com' and it retrieves every conversation — open, closed, and snoozed — including message content, agent assignments, tags, and resolution times. Perfect for getting full context before a customer call.

Can I track support team performance metrics?

Yes. Your AI agent can pull conversation counts, average response times, resolution rates, and open ticket volumes — giving managers instant visibility into team workload and SLA compliance without building custom reports or opening the Intercom analytics dashboard.

Is my customer data secure?

Your Access Token is a private app token that only accesses data in your own Intercom workspace. It respects your workspace's permission model — the token only has access to the scopes you explicitly grant. All API calls are made over HTTPS, and the token is never shared with third parties.

Intercom MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Intercom
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Intercom as an MCP tool provider through the 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 Intercom. "
            "You have 10 tools available."
        ),
    )

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

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 Intercom MCP Server

Connect Intercom to your AI agent and manage your customer communications and support operations conversationally.

LlamaIndex agents combine Intercom tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Conversation Management — List, search, and manage customer conversations with status, assignment, and SLA data.
Contact Search — Query your customer database by email, name, company, or custom attributes to find specific users.
Company Data — Retrieve company profiles, plan information, and aggregate usage metrics.
Support Analytics — Pull conversation counts, response times, and resolution metrics for team performance reviews.

The Intercom MCP Server exposes 10 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 Intercom to LlamaIndex via MCP

Follow these steps to integrate the Intercom 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 10 tools from Intercom

Why Use LlamaIndex with the Intercom MCP Server

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

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

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

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

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

Intercom + LlamaIndex Use Cases

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

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

Data enrichment: query Intercom 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 Intercom for fresh data

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

Intercom MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Intercom to LlamaIndex via MCP:

get_contact

Get contact details

get_conversation

Get conversation thread

list_admins

List team members

list_articles

List help center articles

list_companies

List all companies

list_contacts

List all contacts/leads

list_conversations

List all conversations

list_tags

List all tags

reply_to_conversation

Reply to a conversation

search_contacts

Search contacts by criteria

Example Prompts for Intercom in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Intercom immediately.

"Find the contact record for sarah@startup.io."

"How many open conversations do we have right now?"

"List all companies on our Enterprise plan."

Troubleshooting Intercom MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Intercom + LlamaIndex FAQ

Common questions about integrating Intercom 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.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Intercom tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.