Admin MCP Server

Connect AI assistants to Front via the Admin MCP server

Front's Admin MCP server (mcp.frontapp.com/admin-mcp) lets AI agents manage your Front configuration through a single OAuth-authenticated endpoint. Agents can set up AI teammates, author knowledge, build rules, and manage inboxes, tags, templates, teammates, and more. Agents authenticate as a specific Front admin, and can only reach what that admin can manage. The Admin MCP server is separate from the Front MCP server, which works with conversation data on behalf of any teammate.

This article covers how to connect any MCP-compatible client to the Admin MCP server using an OAuth app you create yourself in the Front developer settings. For the user-facing overview and use case inspiration for Front admins, see the general Help Center article on the Admin MCP server.

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The Admin MCP server is in open beta

The Admin MCP server is free on all plans during the beta. Tool names and parameters may change before general availability.

Looking for examples before you build?

The MCP space in the Front Community has workflow walkthroughs, sample prompts, and more. You can also start up discussions about the Admin MCP server with fellow users and our team.

Overview

Endpointhttps://mcp.frontapp.com/admin-mcp
TransportStreamable HTTP (stateless)
MCP spec version2025-11-25
AuthOAuth 2.1 + PKCE compatibility

Note: Front does not support Dynamic Client Registration. Your AI assistant must support a confidential connection that sends an OAuth client ID and secret. Some popular AI assistants are currently not compatible.
Identity modelPer-user tokens. Every tool call attributes to a specific Front admin
Who can connectCompany admins and workspace admins
Scopesread, write

The connected agent can only manage what the authorizing admin can manage. Company admins can work across the whole company, while workspace admins can only change the workspaces they administer and don't see tools for company-level resources such as AI teammates, knowledge bases, or custom fields. Changes made through the Admin MCP server show in your audit log under the admin who authorized the connection.

Incompatibility list

Some AI assistants do not support confidential connections. These clients cannot connect to the Front Admin MCP server:

  • Any client that requires Dynamic Client Registration (DCR)

Use cases

A few patterns this surface unlocks:

  • Set up an Autopilot AI teammate end to end. Have your AI assistant read an inbox's resolved conversations to learn what to automate, then create the AI teammate, write its instructions, tone, and playbooks, connect a knowledge source, and build the rule that routes conversations to it.
  • Tune AI teammates after launch. Pull improvement opportunities and Replies Hub data, figure out whether a failure is a knowledge gap or a guidance problem, then edit the article, playbook, or instructions that caused it. Simulation sets and success criteria let you track whether a fix worked.
  • Author and publish knowledge. Create knowledge bases, categories, and articles, edit them in bulk, and publish them so AI teammates can answer from them.
  • Build and maintain workspace configuration. Create or update rules (including branching rules and SLA or CSAT recipes), inboxes, tags, message templates, views, custom fields, task templates, shifts, and teammate groups by describing what you need instead of clicking through settings.
  • Connect AI teammates to your other systems. Build custom application connectors, test their requests against the third-party API, and attach them to playbooks.

Set up the Admin MCP server connection

Connecting an AI assistant to Front's Admin MCP server has two general steps: create a Front developer app with the Front Admin MCP feature, and then connect your AI client using the app's credentials.

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After you complete these two steps, other admins at your company will be able to find the Front Admin MCP server in your AI assistant and connect to it without having to create a developer app or configure the connection details on the AI client side.

1. Set up the Front developer app with the Front Admin MCP feature

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These instructions are completed in your Front settings (Settings > Company > Developer)

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You need a dedicated developer app for the Admin MCP server. An app can't use both the Front MCP server and the Admin MCP server, so don't reuse an app you set up for the Front MCP server.

  1. Create a developer app and give it an appropriate name (e.g. "Claude Admin MCP Connector").
  2. Click Add feature in the Features tab and select Front Admin MCP.
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    If Front Admin MCP isn't in the list, refresh the page.

  3. Note the Client ID and Client secret.
  4. Add a redirect URL that corresponds to the AI assistant you're sending data to. For example, as of this writing, the Claude documentation instructs you to use https://claude.ai/api/mcp/auth_callback for most versions of Claude. If you're using Claude Code or similar CLI, you should enter http://localhost/callback. This URL will allow you to connect to a randomly generated local port.
  5. Under Resource permissions, select the resources available to the Admin MCP server and whether the agent can read or write each one. Besides the resources you may know from the Front MCP server, the Admin MCP feature includes ai_agents, ai_resources (playbooks, tones, and knowledge sources), applications, macros, and task_templates.
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    Request the narrowest set that covers your use case. An agent that only audits or reports on your configuration needs read. Only grant write on the resources your agent will actually change.

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    Remember that despite the permissions selected in the OAuth client, agents connecting to the Admin MCP server will be further limited by the subset of data and permissions that the admin who connects the agent has access to.

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    If you change the resource permissions after the initial setup, you must disconnect and re-authorize your connection with your AI assistant ("Connect your AI Assistant" steps) before the new permissions take effect.

  6. Save the app.

2. Connect your AI assistant

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These instructions are completed in your AI assistant, not Front

Once the app is configured, connect from your MCP client so that you and your team can view the Front Admin MCP server. Once it is set up for your company, individual admins can find the server in the list of connectors and authorize it for their own accounts, without configuring the server URL and credentials described in this section.

The exact configuration syntax for initial configuration varies by AI client, but every client will need:

  • The Admin MCP server URL: https://mcp.frontapp.com/admin-mcp
  • Your app's client_id and client_secret
  • The OAuth scope the app should request. Either leave this blank or supply feature:admin_mcp if you need to input a value
  • If your AI assistant requests information about our OAuth URLs, use the following values:
    URLValue
    Authorizationhttps://app.frontapp.com/oauth/authorize
    Token & refresh URLhttps://app.frontapp.com/oauth/token
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Use the UI or command line to connect the Admin MCP server
We recommend using your AI assistant's UI menus to connect the Front Admin MCP server, or terminal commands for CLI assistants. Configuring JSON files is not recommended for most users because varying local paths and environment settings can cause issues. We've provided examples for Claude and ChatGPT below, plus a general JSON shape if you have to modify your AI assistant's configuration file directly.

If you have issues connecting the Admin MCP server, please reach out to your AI assistant's support team and share this documentation with them so they can recommend the correct steps.

Example for Claude (Web and Desktop)

  1. Open Settings and navigate to the Connectors tab (or the Customize page).
  2. Click + and then Add custom connector.
  3. Enter the server URL: https://mcp.frontapp.com/admin-mcp
  4. Click Advanced settings and enter your OAuth Client ID and Client Secret.
  5. Click Add and complete the OAuth authentication flow.
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    You may have to close out Claude and re-open it before it sees the new MCP server and has you authorize permissions.

Example for Claude Code

  1. In Front, make sure your developer app contains the http://localhost/callback redirect URL.
  2. In your terminal, run the following command and enter your client secret when prompted:
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    Including MCP_CLIENT_SECRET is optional. If you don't include it, Claude should prompt you for it after. If it fails to do so, then include it inline.

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    You can name the server something other than front-admin. If you connect to more than one Front company, give each connection a unique name, such as front-admin-<company name>.

   MCP_CLIENT_SECRET=<your-client-secret> claude mcp add --transport http --client-id <your-client-id> --client-secret front-admin https://mcp.frontapp.com/admin-mcp
  1. Exit Claude and re-open it in your terminal so that it pulls the latest list of servers.
  2. Run /mcp to see a list of MCP servers.
  3. Select the server you added and choose to Authenticate it.
  4. Authorize in your browser.

Example for ChatGPT

  1. In ChatGPT settings, turn on developer mode.
  2. In Plugins, click + and enter the server URL: https://mcp.frontapp.com/admin-mcp
  3. Open the advanced OAuth settings and enter your OAuth Client ID and Client Secret.
  4. Copy the callback URL ChatGPT shows and add it as a redirect URL in your Front developer app.
  5. Complete the OAuth authentication flow.

Example for generic MCP server config (confirm with your client's docs on exactly how you structure and pass these properties) - Not recommended for most users

{
  "mcpServers": {
    "front-admin": {
      "url": "https://mcp.frontapp.com/admin-mcp",
      "transport": "streamable-http",
      "oauth": {
        "client_id": "<your-client-id>",
        "client_secret": "<your-client-secret>",
        "scopes": ["read", "write"]
      }
    }
  }
}

Tips for authorization

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Match your client's requested scopes to your OAuth app. By default, many AI assistants (including Claude) will request every scope the Admin MCP server supports. If those scopes exceed what you enabled on the Front developer app, the authorization flow may return an error.
If you encounter this error, configure your client to only request the scopes your app is set up for. In Claude, for example, this is set in the client's JSON config. See Claude's docs on restricting OAuth scopes for the exact syntax. Other clients have similar settings; check their documentation if you hit an authorization error.

When the client first connects, each admin will be redirected to Front to log in and consent. The resulting token is bound to that specific Front admin, and they can only manage what their Front role allows. AI teammates can't authorize the Admin MCP server.

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A note on enterprise deployment: If your AI assistant is centrally managed (e.g. Claude Enterprise, ChatGPT Enterprise), your IT team may need to allow the connection or distribute the app credentials. Each admin still completes the OAuth consent flow individually. This is how Front guarantees that every tool call has a real, attributable admin behind it.

Which tools you'll see

Not every admin sees every tool. Workspace admins don't see tools for company-level resources, and some tools only appear when your plan or account includes the matching feature. For example, shift tools need the Shifts feature, simulation tools need Autopilot, and connector-building tools need custom application connectors.

Getting access to new tools

When Front adds a tool that needs a permission your connection doesn't have yet, the tool appears in your AI assistant, but calling it returns a missing required scopes error. That's because a connection keeps the permissions that were approved when it was first authorized; it doesn't pick up new ones on its own.

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  1. A Front admin opens your developer app (Settings > Company > Developer), opens its Front Admin MCP feature, and enables the new permission under Resource permissions. The error message names the permission the tool needs.
  2. Each admin disconnects Front in their AI assistant and connects it again.
    Until both steps are done, the new tool keeps returning the error. Other tools keep working.

Rate limits

The Admin MCP server allows 200 tool calls per minute per company, on every plan. Every admin, AI assistant, and developer app at your company shares this limit, and every tool call counts the same regardless of which tool it is.

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We'll revisit this limit before general availability based on usage during the beta.

How to handle a limit

When your company goes over the limit, the call fails with an MCP error that says how long to wait:

Admin MCP is limited to 200 tool calls per minute per company. Retry after Xs.

Wait the stated time before retrying. Earlier retries will simply be rejected again.

Tool reference

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The Admin MCP server currently exposes the following tools. Each tool's full input schema is available to your AI assistant through the server. To get the most updated list, ask your AI agent to refresh the tool list, or reconnect.
The Access column shows who can use each tool. Workspace-scoped tools are available to workspace admins, but only for the workspaces they administer. Edits and other write tools that change state in user-visible ways carry destructiveHint: true, which prompts MCP clients to request per-call user confirmation.

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Reference existing resources by their public ID (for example inb_xxx or tag_xxx). The matching list_* tool returns them.


Identity and feedback

ToolTypeAccessDescription
get_my_identityReadAny adminReturns the calling admin's identity and the connected Front company's public ID, name, and slug. Takes no arguments.
send_feedbackWriteAny adminSends feedback about the Admin MCP server to Front, such as a missing tool or one that misbehaved. Changes nothing in your Front.

Conversations

These tools let an admin study an inbox's history before automating it. They return only what the admin can see in Front, and always search across all inboxes the admin can access.

ToolTypeAccessDescription
search_conversationsReadAny adminSearches conversations by query and/or filters: inbox, assignee, team, tags, type, status, snoozed, and an updated date range. IDs in filters must include their prefix.
read_conversationReadAny adminReturns a conversation's header and a paginated, newest-first timeline of messages, comments, and activity. Message entries carry a preview of the body.
read_messageReadAny adminFetches one message with its full body (quoted replies stripped), recipients, attachments, and author.

AI teammates

ToolTypeAccessDescription
list_ai_teammatesReadAny adminLists AI teammates with their ID (atc_xxx), kind (Autopilot or external), and status (live or paused).
get_ai_teammateReadAny adminReads one AI teammate's configuration, including its linked knowledge sources and playbooks. Can also return its instructions.
create_ai_teammateWriteGlobal adminCreates an Autopilot or external (BYOA) AI teammate. Escalation settings are still set in Front, and an external AI teammate needs a connection secret generated in Front before it can call Front back. AI teammates can't be deleted.
edit_ai_teammateWrite (destructive)Global adminUpdates an AI teammate's name, handle, description, avatar, webhook URL, escalation timeout, workspaces, and status. For Autopilot, also sets its instructions, tone, playbooks, and knowledge sources. Pausing an AI teammate escalates its assigned conversations to people.
list_ai_teammate_tonesReadGlobal adminLists the tones an Autopilot AI teammate can answer in, including Front's built-in tones and your company's own.
get_ai_teammate_toneReadGlobal adminReads one tone in full.
create_ai_teammate_toneWriteGlobal adminCreates a company tone from a title, description, and body. Apply it to an AI teammate with edit_ai_teammate.
edit_ai_teammate_toneWrite (destructive)Global adminEdits a company tone in place. Every AI teammate using it picks up the change on its next reply. Built-in tones are read-only.
list_ai_teammate_playbooksReadGlobal adminLists playbooks by title and description. Pass an AI teammate ID to list only the playbooks it follows.
get_ai_teammate_playbookReadGlobal adminReads one playbook in full, including its steps and connectors.
create_ai_teammate_playbookWriteGlobal adminCreates a playbook from a title, description, steps, and connectors. The description decides when the playbook gets loaded, so it matters. Attach it to an AI teammate with edit_ai_teammate.
edit_ai_teammate_playbookWrite (destructive)Global adminEdits a playbook's title, description, steps, or connectors in place. Every AI teammate following it picks up the change on its next reply.
list_connectorsReadGlobal adminLists installed apps whose tools an Autopilot AI teammate can call, with each tool's ID and whether an admin turned it off. Use these IDs in a playbook's connectors.

Knowledge

ToolTypeAccessDescription
list_knowledge_basesReadAny adminLists knowledge bases with their ID, type, status, languages, and published languages.
create_knowledge_baseWriteGlobal adminCreates a knowledge base.
edit_knowledge_baseWrite (destructive)Global adminUpdates a knowledge base's name or configuration.
publish_knowledge_baseWriteGlobal adminPublishes one language of a help center, which also lets AI teammates answer from its articles.
list_knowledge_base_categoriesReadAny adminLists the categories in a knowledge base, including each category's parent.
create_knowledge_base_categoryWriteGlobal adminCreates a category in a knowledge base.
edit_knowledge_base_categoryWrite (destructive)Global adminUpdates a category.
list_knowledge_base_articlesReadAny adminLists articles in a knowledge base, optionally by category or language.
create_knowledge_base_articleWriteGlobal adminCreates an article.
edit_knowledge_base_articleWrite (destructive)Global adminEdits an article's title, body, search terms, or category. Saves a draft, so a published article keeps its current text until it is published.
publish_knowledge_base_articleWriteGlobal adminPublishes one language version of an article. Counts against your plan's published-article limit.
list_knowledge_sourcesReadAny adminLists the knowledge sources assigned to a workspace in AI settings, with their public IDs.
create_knowledge_sourceWriteGlobal adminCreates a website source (crawled after creation) or a note in your notes source. Returns the source ID to link with edit_ai_teammate.
edit_knowledge_sourceWrite (destructive)Global adminUpdates a website source's name, crawl paths, or JavaScript setting. The website address can't be changed, and changes can start a new crawl.

Rules

ToolTypeAccessDescription
list_rulesReadAny adminLists rules, filterable by inbox, tag, type, category, and active status.
get_ruleReadAny adminReads one rule's full configuration, including triggers, conditions, and actions.
create_ruleWriteAny adminCreates a rule with triggers, conditions, and actions, including assigning conversations to an AI teammate.
create_branching_ruleWriteAny adminCreates a branching rule from a plain-English description.
create_complex_ruleWriteAny adminCreates a multi-rule recipe such as an SLA, resolution-time SLA, CSAT survey, Smart QA, Smart CSAT, required tagging, or AI tagging. Only available when enabled for your company.
edit_ruleWrite (destructive)Any adminProposes changes to a rule's triggers, conditions, or actions and returns a draft. Nothing is saved until the tool is called again with confirm_draft_id. Only available when enabled for your company.
edit_branching_ruleWrite (destructive)Any adminProposes changes to a branching rule and returns a draft. Nothing is saved until the tool is called again with confirm_draft_id.
edit_rule_statusWrite (destructive)Any adminEnables or disables any rule, including every rule inside a recipe such as an SLA. Rules are deactivated rather than deleted.

Workspace configuration

ToolTypeAccessDescription
list_workspacesReadAny adminLists workspaces with their teammates and configuration.
get_workspaceReadAny adminReads one workspace.
list_inboxesReadAny adminLists inboxes.
get_inboxReadAny adminReads one inbox: access mode, who has access and how, ticketing, AI status, business hours, and company rules.
create_inboxWriteAny adminCreates a shared inbox.
edit_inboxWrite (destructive)Any adminUpdates an inbox's name or settings.
list_channelsReadAny adminLists channels, filterable by name or address, type, inbox, and status.
get_channelReadAny adminReads one channel.
list_tagsReadAny adminLists tags.
get_tagReadAny adminReads one tag.
create_tagWriteAny adminCreates a tag, optionally nested under a parent tag.
edit_tagWrite (destructive)Any adminRenames or moves a tag.
list_message_templatesReadAny adminLists message templates.
get_message_templateReadAny adminReads one message template.
create_message_templateWriteAny adminCreates a message template.
edit_message_templateWrite (destructive)Any adminUpdates a message template.
list_message_template_foldersReadAny adminLists message template folders.
create_message_template_folderWriteAny adminCreates a message template folder.
edit_message_template_folderWrite (destructive)Any adminUpdates a message template folder.
list_viewsReadAny adminLists views with their inbox, tag, and assignee configuration.
get_viewReadAny adminReads one view.
create_viewWriteAny adminCreates a view.
edit_viewWrite (destructive)Any adminUpdates a view.
list_custom_field_definitionsReadAny adminLists custom field definitions.
get_custom_field_definitionReadAny adminReads one custom field definition.
create_custom_fieldWriteGlobal adminCreates a custom field.
edit_custom_fieldWrite (destructive)Global adminUpdates a custom field.
list_task_templatesReadAny adminLists task templates.
create_task_templateWriteAny adminCreates a task template.
edit_task_templateWrite (destructive)Any adminUpdates a task template.
list_teammatesReadAny adminSearches teammates by name or email.
get_teammateReadAny adminReads one teammate.
invite_teammateWrite (destructive)Global adminInvites a teammate by email, sets whether they are a company admin, and adds them to teammate groups. Sends the invitation and uses a paid seat.
edit_teammateWrite (destructive)Any adminUpdates a teammate's name, username, availability, or account status.
list_teammate_groupsReadAny adminLists teammate groups, optionally with the permissions each grants.
get_teammate_groupReadAny adminReads one teammate group.
create_teammate_groupWriteGlobal adminCreates a teammate group.
edit_teammate_groupWrite (destructive)Global adminUpdates a teammate group.
list_shiftsReadAny adminLists shifts with their hours, teammates, and timezone. Requires the Shifts feature.
get_shiftReadAny adminReads one shift. Requires the Shifts feature.
create_shiftWriteAny adminCreates a shift. Requires the Shifts feature and isn't available with Workforce Management.
edit_shiftWrite (destructive)Any adminUpdates a shift's name, color, timezone, weekly hours, teammates, or enabled status. Requires the Shifts feature and isn't available with Workforce Management.
list_signaturesReadAny adminLists signatures.
get_signatureReadAny adminReads one signature.
list_macrosReadAny adminLists macros.
get_macroReadAny adminReads one macro.
list_statusesReadAny adminLists ticket statuses. Returns empty when ticketing is not enabled.
list_ai_topicsReadAny adminLists the AI topics detected in a workspace. Topics are separate from tags.
list_vacation_respondersReadAny adminLists time off responders with their status, schedule, and channels.
list_contact_listsReadAny adminLists contact lists, for use in rule conditions.

AI teammate evaluation and testing

ToolTypeAccessDescription
list_improvement_opportunitiesReadAny adminLists the improvement opportunities Front found for an AI teammate, most affected first, with the proposed fixes and the ID of the resource each fix would edit.
get_replies_hub_dataReadAny adminReturns AI reply data matching the Replies Hub export, including diagnoses and how sent replies differ from AI-generated ones. Only available when enabled.
regenerate_replyWriteAny adminRegenerates an AI reply on a conversation, to check whether a problem reproduces or a fix worked. Only available when enabled.
list_simulation_setsReadAny adminLists an AI teammate's simulation sets with their last run date and Smart QA scorecard. Requires Autopilot and permission to edit AI teammates.
create_simulation_setWriteGlobal adminCreates a simulation set on an AI teammate, with an optional Smart QA scorecard. Requires Autopilot.
edit_simulation_setWrite (destructive)Global adminRenames a simulation set or changes its Smart QA scorecard. Requires Autopilot.
create_simulationsWriteGlobal adminCreates up to 20 simulations in a simulation set, written from scratch or modelled on a real conversation. When modelled on a conversation, Front fills in anything you leave out and drafts the scenario with AI. The result lists the simulations created and why any others weren't. Requires Autopilot.
edit_simulationWrite (destructive)Global adminChanges a simulation's name, source conversation, first message, scenario, inbox and channel, customer, tags, or success criteria. Changing its content detaches it from the conversation it was modelled on. Runs already scored keep their results. Requires Autopilot.
list_simulationsReadAny adminLists the simulations in a set by name and first message. Requires Autopilot and permission to edit AI teammates.
get_simulationReadAny adminReads one simulation in full: first message, scenario, inbox, contact, tags, and success criteria. Requires Autopilot and permission to edit AI teammates.
run_simulationsWriteAny adminStarts runs of an AI teammate's simulations: all of them by default, or only the sets and simulations you pick. Runs are queued, so the tool returns their IDs before any finish. A simulation that's already running isn't started again. Requires Autopilot and permission to edit AI teammates.
get_simulation_resultsReadAny adminReturns the latest run of each simulation in a set or list: its status, whether it passed, how many criteria it passed, and whether it's a regression or a fix compared to the previous run. Call it again while runs are in progress. Requires Autopilot and permission to edit AI teammates.
get_simulation_runReadAny adminReads one run in full to show why it passed or failed: the simulated conversation, the steps the AI teammate took (resources retrieved, connectors called, instructions followed), how the conversation ended, and each criterion's verdict with the judge's reason. Requires Autopilot and permission to edit AI teammates.
list_success_criteriaReadAny adminLists your company's success criteria with what pass and fail mean. Requires Autopilot and permission to edit AI teammates.
create_success_criterionWriteGlobal adminCreates a success criterion from a name, definition, and pass and fail text. Requires Autopilot.
edit_success_criterionWrite (destructive)Global adminUpdates a success criterion. The change applies to every simulation using it. Requires Autopilot.

Custom application connectors

These tools build the custom applications whose requests AI teammates can call from playbooks. They require custom application connectors on your plan.

ToolTypeAccessDescription
list_local_applicationsReadAny adminLists your company's custom applications.
create_local_applicationWriteGlobal adminCreates a custom application.
create_application_serverWriteGlobal adminAdds a server origin to a custom application.
create_application_requestWriteGlobal adminCreates an app request: its inputs, HTTP steps, and outputs.
edit_application_requestWrite (destructive)Global adminUpdates an app request.
create_application_objectWriteGlobal adminCreates an application object.
list_app_requestsReadGlobal adminLists the app requests on a custom application.
get_app_requestReadGlobal adminReads one app request: name, description, draft state, server origin, and HTTP requests.
check_app_credentialsReadGlobal adminChecks whether a server origin needs credentials. Doesn't create or authorize them.
get_expression_referenceReadGlobal adminExplains the {{ }} expressions some tools accept, such as the references in app requests. Tools that take expressions name the scope to pass.
test_app_requestTestGlobal adminTests an app request, including drafts, by calling the third-party API. This can create, update, or delete data in that system. Sensitive values in the response are redacted.

Troubleshooting

401 Unauthorized on every request

The token is invalid, expired, or has been revoked. Common causes:

  • The admin revoked the app's access in Front's connected apps settings.
  • A company admin uninstalled the OAuth app entirely.
  • The access token expired and the refresh flow didn't fire. Re-authenticate to mint a new token.

missing required scopes on a tool

Your connection doesn't have a permission this tool needs. This usually happens after Front adds a tool. See Getting access to new tools.

This token cannot access the Admin MCP Server

The connection is using a developer app set up for the Front MCP server. Create a separate developer app with the Front Admin MCP feature and connect with its credentials.

The Admin MCP Server requires an admin requester

Only company admins and workspace admins can use the Admin MCP server. Have an admin authorize the connection instead.

A tool is missing or refuses a workspace

Workspace admins only see workspace-level tools and can only change workspaces they administer. Some tools also depend on your plan or features enabled for your company. See Which tools you'll see.

A tool stops working after an admin's Front access changes

Permissions are enforced at call time against the admin's current Front role. If the admin lost admin rights or access to a workspace after authorizing, tools that need that access will fail.

Admin MCP is limited to 200 tool calls per minute per company

Your company went over its shared rate limit. Wait the number of seconds in the error before retrying. If this happens during normal use, look for a polling loop that's tighter than it needs to be, or several agents running at once, since everyone at your company shares the limit. For more details, see the rate limits section.

Feedback & community discussions

To share feedback about tools you'd like to see in the Admin MCP server, please add an idea in our community or vote on an existing one. You can also ask your AI assistant to send feedback directly with the send_feedback tool.

To discuss Admin MCP server use cases and workflows, please create a post in or subscribe to our discussion space.