Sandbox
@reminia/zendesk-mcp-server

Zendesk MCP server for ticket and help center access

This server connects an agent to Zendesk through MCP. It exposes tools for reading and updating tickets, creating comments, and pulling help center articles as knowledge base content. It also includes prompts for analyzing tickets and drafting responses, so the agent can work on support tasks with Zendesk data instead of raw copy-paste.

119 stars83 forksPythonUpdated 21d ago
Who it's for

Builders who want Claude Code or another MCP client to read and update Zendesk directly.

What it delivers

You can handle Zendesk work from your agent with live ticket data, comments, and help center context.

What it does

Ticket tools

Fetch, create, and update Zendesk tickets, including pagination, status, priority, assignee, tags, and custom fields.

Comment tools

Read all comments on a ticket and add new public or private comments.

Help center resource

Expose the Zendesk knowledge base through `zendesk://knowledge-base`.

Ticket prompts

Provide `analyze-ticket` and `draft-ticket-response` prompts for support work.

OAuth authentication

Use per-operator OAuth with token refresh and local token storage.

Docker support

Run the server in a container with environment variables and a mounted token file.

How to get it

  1. 1Copy .env.example to .env and set
    ZENDESK_SUBDOMAIN=acme        # for https://acme.zendesk.com
    ZENDESK_CLIENT_ID=your-client-identifier
  2. 2Two optional settings, both of which must agree with the OAuth client
    uv run zendesk-auth
  3. 3If the browser cannot reach this machine — a remote shell, or an OAuth client registered…
    uv run zendesk-auth --manual
  4. 4Build the image
    docker build -t zendesk-mcp-server .
  5. 5Authorize on the host, not in the container. zendesk-auth needs a browser and a local…
    uv run zendesk-auth
  6. 6Run the server, passing the environment file and mounting the token store
    docker run --rm \
      --env-file /path/to/.env \
      --user "$(id -u):$(id -g)" \
      -e ZENDESK_TOKEN_FILE=/tokens/tokens.json \
      -v "$HOME/.config/zendesk-mcp:/tokens" \
      zendesk-mcp-server

README

Zendesk MCP Server

ci License

A Model Context Protocol server for Zendesk.

This server provides a comprehensive integration with Zendesk. It offers:

  • Tools for retrieving and managing Zendesk tickets and comments
  • Specialized prompts for ticket analysis and response drafting
  • Full access to the Zendesk Help Center articles as knowledge base

demo

Setup

  • build: uv venv && uv pip install -e . or uv build in short.
  • configure authentication: see Authentication below.
  • configure in Claude desktop:
{
  "mcpServers": {
      "zendesk": {
          "command": "uv",
          "args": [
              "--directory",
              "/path/to/zendesk-mcp-server",
              "run",
              "zendesk"
          ]
      }
  }
}

Authentication

This server authenticates with OAuth. Each operator authorizes with their own Zendesk login, so API calls carry their identity and Zendesk applies exactly the permissions it applies in the UI — their role, their group restrictions, their ticket access. Comments they post are authored by them.

API token authentication still works but is deprecated. See Migrating from an API token.

1. Register a public OAuth client

In Admin Center, go to Apps and integrations > APIs > OAuth clients and create a client:

FieldValue
Client kindPublic — this server runs on each operator's machine, so there is no secret it could keep. PKCE is used instead.
Redirect URLshttp://localhost:4567/callback
Allowed scopestickets:read tickets:write ticket_attachments:read users:read hc:read

Setting Allowed scopes is optional but recommended: it caps what any token from this client can ever request, even if the code changes.

Note the client's Identifier — that is the ZENDESK_CLIENT_ID below.

If Zendesk rejects http://localhost:4567/callback, register https://localhost instead and use zendesk-auth --manual in step 3.

2. Configure the environment

Copy .env.example to .env and set:

ZENDESK_SUBDOMAIN=acme        # for https://acme.zendesk.com
ZENDESK_CLIENT_ID=your-client-identifier

Keep .env out of version control.

Two optional settings, both of which must agree with the OAuth client:

VariableDefaultWhen to change it
ZENDESK_OAUTH_REDIRECT_URIhttp://localhost:4567/callbackPort 4567 is in use, or the client is registered with a different redirect URL. Must match a redirect URL on the client exactly.
ZENDESK_TOKEN_FILE$XDG_CONFIG_HOME/zendesk-mcp/tokens.jsonStoring tokens elsewhere, for example a Docker volume.

3. Authorize this machine, once

uv run zendesk-auth

This opens a browser, asks the operator to approve access, and stores the resulting tokens locally. From then on the server renews access on its own; the operator never repeats this unless the tokens are revoked or left unused past the refresh token's lifetime (90 days as requested by this server).

If the browser cannot reach this machine — a remote shell, or an OAuth client registered with https://localhost — use the paste-based flow instead:

uv run zendesk-auth --manual

Tokens are written to $XDG_CONFIG_HOME/zendesk-mcp/tokens.json (~/.config/zendesk-mcp/tokens.json by default), created 0600 inside a 0700 directory. Override the location with ZENDESK_TOKEN_FILE. The file holds live credentials: treat it like a password and never commit it.

How token renewal works

Zendesk access tokens are short-lived — 30 minutes by default, 48 hours at most — so the server refreshes them for you:

  • before expiry, when the stored token is within 60 seconds of expiring, and
  • on rejection, when Zendesk answers 401 with {"error": "invalid_token"}, in which case the request is retried once with a fresh token.

Only invalid_token triggers a retry. A 401 or 403 from insufficient scope or from the operator's own Zendesk permissions is passed through unchanged, so permission problems stay visible instead of looking like auth flakiness.

Each refresh rotates the refresh token and invalidates the previous one immediately, so the new pair is written to disk before it is used. Writes are atomic and guarded by a lock file, which matters if you run the server from more than one MCP client at the same time.

When the refresh token itself is expired or revoked, tools fail with a message telling the operator to re-run zendesk-auth.

Choosing scopes

The default scopes cover every tool this server exposes:

ScopeNeeded for
tickets:readget_ticket, get_tickets, get_ticket_comments
tickets:writecreate_ticket, update_ticket, create_ticket_comment
ticket_attachments:readget_ticket_attachment
users:readrequester and assignee details on tickets
hc:readthe zendesk://knowledge-base resource

Narrow them with ZENDESK_OAUTH_SCOPES if you do not need every tool — for read-only access, tickets:read users:read hc:read.

Scopes are a ceiling, not a grant: a token can never do more than the authorizing operator is allowed to do. Note that Zendesk accepts unrecognised scope names when issuing a token but then rejects every request with 403, so zendesk-auth prints the scope Zendesk actually granted for comparison.

Migrating from an API token

Zendesk is retiring API tokens on this schedule:

DateChange
2026-07-28Tokens unused for 30 days are deactivated automatically; new accounts cannot create tokens.
2026-10-27No account can create new API tokens.
2027-04-30All API tokens stop working permanently.

Until then ZENDESK_EMAIL + ZENDESK_API_KEY continue to work, and the server logs a deprecation warning the first time it authenticates. Set ZENDESK_CLIENT_ID and OAuth takes precedence, so you can migrate without removing the old variables.

Beyond the deadline, there is a reason to move sooner: a Zendesk API token is account-level and unscoped. Whoever holds it gets the full access of the user it is paired with, which for most installations is an admin. That is what per-operator OAuth fixes.

Why not the client credentials flow? It is simpler — no browser step, no refresh tokens — but its tokens are attributed to the Zendesk user who created the OAuth client. Every operator would act as that one user, usually an admin, and audit logs and comment authorship would all point at them. Since the goal is for operators to have exactly their own Zendesk permissions, the authorization code flow is the only one that fits.

Docker

You can containerize the server if you prefer an isolated runtime:

  1. Copy .env.example to .env and fill in your Zendesk configuration. Keep this file outside version control.

  2. Build the image:

    docker build -t zendesk-mcp-server .
    
  3. Authorize on the host, not in the container. zendesk-auth needs a browser and a local callback port, so run it once outside Docker:

    uv run zendesk-auth
    
  4. Run the server, passing the environment file and mounting the token store:

    docker run --rm \
      --env-file /path/to/.env \
      --user "$(id -u):$(id -g)" \
      -e ZENDESK_TOKEN_FILE=/tokens/tokens.json \
      -v "$HOME/.config/zendesk-mcp:/tokens" \
      zendesk-mcp-server
    

    The mount must be writable: the server rewrites the file every time it rotates the refresh token, and a read-only mount will strand it on an expired token. --user makes the container run as you, so it can read the 0600 token file created on the host.

    Add -i when wiring the container to MCP clients over STDIN/STDOUT (Claude Code uses this mode). For daemonized runs, add -d --name zendesk-mcp.

The image installs dependencies from requirements.lock and drops privileges to a non-root user. With API token authentication no volume is needed, since configuration comes entirely from environment variables.

Claude MCP Integration

To use the Dockerized server from Claude Code/Desktop, add an entry to Claude Code's settings.json similar to:

{
  "mcpServers": {
    "zendesk": {
      "command": "/usr/local/bin/docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "--env-file",
        "/path/to/zendesk-mcp-server/.env",
        "zendesk-mcp-server"
      ]
    }
  }
}

Adjust the paths to match your environment. After saving the file, restart Claude for the new MCP server to be detected.

Development

Run the test suite:

uv pip install -e '.[test]'
pytest

The tests use mocked HTTP and never contact Zendesk. They cover the API-token and OAuth paths, PKCE derivation, token storage and rotation, and each of the four ways this server calls Zendesk.

Resources

  • zendesk://knowledge-base, get access to the whole help center articles.

Prompts

analyze-ticket

Analyze a Zendesk ticket and provide a detailed analysis of the ticket.

draft-ticket-response

Draft a response to a Zendesk ticket.

Tools

get_tickets

Fetch the latest tickets with pagination support

  • Input:

    • page (integer, optional): Page number (defaults to 1)
    • per_page (integer, optional): Number of tickets per page, max 100 (defaults to 25)
    • sort_by (string, optional): Field to sort by - created_at, updated_at, priority, or status (defaults to created_at)
    • sort_order (string, optional): Sort order - asc or desc (defaults to desc)
  • Output: Returns a list of tickets with essential fields including id, subject, status, priority, description, timestamps, and assignee information, along with pagination metadata

get_ticket

Retrieve a Zendesk ticket by its ID

  • Input:
    • ticket_id (integer): The ID of the ticket to retrieve

get_ticket_comments

Retrieve all comments for a Zendesk ticket by its ID

  • Input:
    • ticket_id (integer): The ID of the ticket to get comments for

create_ticket_comment

Create a new comment on an existing Zendesk ticket

  • Input:
    • ticket_id (integer): The ID of the ticket to comment on
    • comment (string): The comment text/content to add
    • public (boolean, optional): Whether the comment should be public (defaults to true)

create_ticket

Create a new Zendesk ticket

  • Input:
    • subject (string): Ticket subject
    • description (string): Ticket description
    • requester_id (integer, optional)
    • assignee_id (integer, optional)
    • priority (string, optional): one of low, normal, high, urgent
    • type (string, optional): one of problem, incident, question, task
    • tags (array[string], optional)
    • custom_fields (array[object], optional)

update_ticket

Update fields on an existing Zendesk ticket (e.g., status, priority, assignee)

  • Input:
    • ticket_id (integer): The ID of the ticket to update
    • subject (string, optional)
    • status (string, optional): one of new, open, pending, on-hold, solved, closed
    • priority (string, optional): one of low, normal, high, urgent
    • type (string, optional)
    • assignee_id (integer, optional)
    • requester_id (integer, optional)
    • tags (array[string], optional)
    • custom_fields (array[object], optional)
    • due_at (string, optional): ISO8601 datetime

Files in the repo

Repository payload12 top-level entries
  • .github
  • src
  • tests
  • .env.example
  • .gitignore
  • .python-version
  • Dockerfile
  • LICENSE
  • pyproject.toml
  • README.md
  • requirements.lock
  • uv.lock

Discussion (0)

Ask about usage, or say what you built with it

Sign in to join the discussion.

No comments yet. Be the first to say what this is good for.

More connectors

Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface

86k

Universal provider proxy for OpenAI Codex & Claude Code — use any LLM (Claude, Gemini, Grok, DeepSeek, Ollama…) with Codex CLI, App, SDK, and Claude Code

14k
okf-memory/
okf-agent-memory

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

547

Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

62k
1 add

Open-source auth gateway connecting 1400+ SaaS providers to AI agents through SDK, CLI, MCP, HTTP, and OpenAPI.

5.7k

Open-source 3D architectural editor with a local CLI, MCP tools, and practical workflows for humans and AI agents.

23k