Zendesk

Live

API KEY

SUPPORT

Enterprise support runs on Zendesk: tickets, SLAs, and customer organizations. Your agent can read ticket history, update fields, and look up organizations, scoped to the agent's queue.

  • Acts as the agent: Ticket access and actions stay tied to the Zendesk agent who authorized the workflow.
  • Credentials stay vaulted: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: Agent permissions enforced. 90-day audit trail.
Zendesk
agent · Acme Q3
Run
List all urgent tickets unassigned in the last 24 hours.
S
zendesk_search_tickets
74ms
Zendesk agent
4 urgent unassigned tickets: #1042 (login failure, 6h), #1039 (billing error, 11h), #1035 (data export broken, 18h), #1031 (API timeout, 22h).
Sources: 4 tickets, last 24 hours
zendeskmcp
4 tickets
18:29
Message Claude...

Tools your Zendesk agent reaches for, scoped per user.

CALL ANY TOOL
Create, update, reply, and search tickets. Manage users and organizations. Same toolkit, every framework, no auth plumbing.
zendesk_search_tickets
Search tickets
Search Zendesk tickets using full Zendesk query syntax with pagination (max 1,000 results).
Parameters
Name
Type
Required
Description
query
string
Required
Search query using Zendesk syntax (e.g. status:open priority:urgent)
page
number
Optional
Pagination page number
per_page
number
Optional
Results per page, max 100
sort_by
string
Optional
Sort field
sort_order
string
Optional
Sort direction: asc or desc
zendesk_ticket_create
Create ticket
zendesk_ticket_get
Get ticket
zendesk_ticket_reply
Reply to ticket
zendesk_ticket_update
Update ticket
zendesk_ticket_comments_list
List ticket comments
Build your Agent
Drop the toolkit in, point it at the agent, and your automation can triage, reply, and escalate Zendesk tickets from the first run.
import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["zendesk"], toolNames: ["zendesk_search_tickets", "zendesk_ticket_get", "zendesk_ticket_reply"] },
pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
name: t.tool.definition.name,
description: t.tool.definition.description,
schema: t.tool.definition.input_schema,
func: async (args) => sk.tools.executeTool({
toolName: t.tool.definition.name, identifier: "user_123", toolInput: args,
}),
}));

const agent = createReactAgent({ llm, tools: lcTools });
import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["zendesk"], toolNames: ["zendesk_search_tickets", "zendesk_ticket_get", "zendesk_ticket_reply"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
type: "function",
function: {
name: t.tool.definition.name,
description: t.tool.definition.description,
parameters: t.tool.definition.input_schema,
},
}));

const resp = await openai.responses.create({
model: "gpt-4o", input: prompt, tools: llmTools,
});
import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["zendesk"], toolNames: ["zendesk_search_tickets", "zendesk_ticket_get", "zendesk_ticket_reply"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
name: t.tool.definition.name,
description: t.tool.definition.description,
input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
model: "claude-sonnet-4-6", max_tokens: 1024,
tools: llmTools,
messages: [{ role: "user", content: prompt }],
});
import { Agent } from "@google/adk/agents";
import {
MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
connectionParams: new StreamableHTTPConnectionParams({
url: "https://mcp.scalekit.com/zendesk",
headers: { Authorization: `Bearer ${userScopedToken}` },
}),
});

const agent = new Agent({
name: "agent", model: "gemini-2.0-flash",
tools: await toolset.getTools(),
});
Try these prompts
Paste any prompt into your agent to automate Zendesk support workflows.
Triage & escalation
Copy the prompt
Copied
List all urgent tickets unassigned in the last 24 hours.
Copy the prompt
Copied
Which open tickets have no reply in more than 48 hours?
Copy the prompt
Copied
Find all tickets tagged [bug] with priority high.
Copy the prompt
Copied
Show me all tickets from [customer name].
Action & replies
Copy the prompt
Copied
Reply to ticket #[id]: [response text].
Copy the prompt
Copied
Assign ticket #[id] to [agent email].
Copy the prompt
Copied
Close all solved tickets older than 30 days.
Copy the prompt
Copied
Add tag [escalated] to ticket #[id].
Reporting & insights
Copy the prompt
Copied
How many open tickets are there by priority?
Copy the prompt
Copied
List all tickets created today grouped by type.
Copy the prompt
Copied
What is the average first reply time this week?
Copy the prompt
Copied
Show all tickets assigned to [agent name] with status open.
SEE HOW AUTH WORKS
Users authorize Zendesk once. Their help desk credentials stay vaulted, every call is checked, and every action is logged.
1
Authorize
Your user connects
Zendesk
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
A’s meetings only
2
Store
Their
Zendesk
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Zendesk
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Zendesk
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across Freshdesk and other support connectors.
SUPPORT
Support ticket automation (Google ADK)
Google ADK agent that classifies Zendesk tickets, pulls Notion context, and posts to Slack. End-to-end ticket handoff.
SUPPORT
Support triage agent
Read Zendesk tickets, fetch runbooks from Notion, and route to the right Slack channel with a drafted response.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought. Scalekit starts with agent identity, scope enforcement, and audit.
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.
// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Zendesk today. Others tomorrow.
Capability
DIY
Scalekit AgentKit
Token storage
Build + maintain yourself
AES-256 vault, managed
Per-user isolation
Custom credential map
Per-tenant namespace, default
Scope enforcement
Manual checks or none
Per-request, pre-API call
Token refresh
Cron job you maintain
Automatic
Audit trail
Build your own logging
90-day, SIEM-exportable
New connector
New OAuth implementation
Same pattern, one config
Multi-framework
Per-framework adapter code
8 adapters included
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""zendesk"": {
""url"": ""https://mcp.scalekit.com/zendesk"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.zendesk]
url = ""https://mcp.scalekit.com/zendesk""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""zendesk"": {
""url"": ""https://mcp.scalekit.com/zendesk"",
""type"": ""http""
}
}
}
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""zendesk"": {
""url"": ""https://mcp.scalekit.com/zendesk"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Windsurf Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""zendesk"": {
""url"": ""https://mcp.scalekit.com/zendesk"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.zendesk]
url = ""https://mcp.scalekit.com/zendesk""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""zendesk"": {
""url"": ""https://mcp.scalekit.com/zendesk"",
""type"": ""http""
}
}
}