LINE Bot MCP Server
OfficialProvides tools for interacting with the LINE Messaging API, enabling AI agents to send push and broadcast messages (text and flex), retrieve user profiles, manage message quotas, create and manage rich menus, and get follower IDs for a LINE Official Account.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@LINE Bot MCP ServerPush a text message to user U123 saying 'Hello'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
LINE Bot MCP Server
Model Context Protocol (MCP) server implementation that integrates the LINE Messaging API to connect an AI Agent to the LINE Official Account.

This repository is provided as a preview version. While we offer it for experimental purposes, please be aware that it may not include complete functionality or comprehensive support.
Tools
push_text_message
Push a simple text message to a user via LINE.
Inputs:
userId(string?): The user ID to receive a message. Defaults to DESTINATION_USER_ID. EitheruserIdorDESTINATION_USER_IDmust be set.message.text(string): The plain text content to send to the user.
push_flex_message
Push a highly customizable flex message to a user via LINE.
Inputs:
userId(string?): The user ID to receive a message. Defaults to DESTINATION_USER_ID. EitheruserIdorDESTINATION_USER_IDmust be set.message.altText(string): Alternative text shown when flex message cannot be displayed.message.contents(any): The contents of the flex message. This is a JSON object that defines the layout and components of the message.message.contents.type(enum): Type of the container. 'bubble' for single container, 'carousel' for multiple swipeable bubbles.
broadcast_text_message
Broadcast a simple text message via LINE to all users who have followed your LINE Official Account.
Inputs:
message.text(string): The plain text content to send to the users.
broadcast_flex_message
Broadcast a highly customizable flex message via LINE to all users who have added your LINE Official Account.
Inputs:
message.altText(string): Alternative text shown when flex message cannot be displayed.message.contents(any): The contents of the flex message. This is a JSON object that defines the layout and components of the message.message.contents.type(enum): Type of the container. 'bubble' for single container, 'carousel' for multiple swipeable bubbles.
get_profile
Get detailed profile information of a LINE user including display name, profile picture URL, status message and language.
Inputs:
userId(string?): The ID of the user whose profile you want to retrieve. Defaults to DESTINATION_USER_ID.
get_message_quota
Get the message quota and consumption of the LINE Official Account. This shows the monthly message limit and current usage.
Inputs:
None
get_rich_menu_list
Get the list of rich menus associated with your LINE Official Account.
Inputs:
None
delete_rich_menu
Delete a rich menu from your LINE Official Account.
Inputs:
richMenuId(string): The ID of the rich menu to delete.
set_rich_menu_default
Set a rich menu as the default rich menu.
Inputs:
richMenuId(string): The ID of the rich menu to set as default.
cancel_rich_menu_default
Cancel the default rich menu.
Inputs:
None
create_rich_menu
Create a rich menu based on the given actions. Generate and upload an image. Set as default.
Inputs:
chatBarText(string): Text displayed in chat bar, also used as rich menu name.actions(array): The actions of the rich menu. You can specify minimum 1 to maximum 6 actions. Each action can be one of the following types:postback: For sending a postback actionmessage: For sending a text messageuri: For opening a URLdatetimepicker: For opening a date/time pickercamera: For opening the cameracameraRoll: For opening the camera rolllocation: For sending the current locationrichmenuswitch: For switching to another rich menuclipboard: For copying text to clipboard
get_follower_ids
Get a list of user IDs of users who have added the LINE Official Account as a friend. This allows you to obtain user IDs for sending messages without manually preparing them.
Inputs:
start(string?): Continuation token to get the next array of user IDs. Returned in thenextproperty of a previous response.limit(number?): The maximum number of user IDs to retrieve in a single request.
Related MCP server: LineWhiz
Installation (Using npx)
requirements:
Node.js v22 or later
Step 1: Create LINE Official Account
This MCP server utilizes a LINE Official Account. If you do not have one, please create it by following this instructions.
If you have a LINE Official Account, enable the Messaging API for your LINE Official Account by following this instructions.
Step 2: Configure AI Agent
Please add the following configuration for an AI Agent like Claude Desktop or Cline.
Set the environment variables or arguments as follows:
CHANNEL_ACCESS_TOKEN: (required) Channel Access Token. You can confirm this by following this instructions.DESTINATION_USER_ID: (optional) The default user ID of the recipient. If the Tool's input does not includeuserId,DESTINATION_USER_IDis required. You can confirm this by following this instructions.
{
"mcpServers": {
"line-bot": {
"command": "npx",
"args": [
"@line/line-bot-mcp-server"
],
"env": {
"NPM_CONFIG_IGNORE_SCRIPTS": "true",
"CHANNEL_ACCESS_TOKEN" : "FILL_HERE",
"DESTINATION_USER_ID" : "FILL_HERE"
}
}
}
}Installation (Using Docker)
Step 1: Create LINE Official Account
This MCP server utilizes a LINE Official Account. If you do not have one, please create it by following this instructions.
If you have a LINE Official Account, enable the Messaging API for your LINE Official Account by following this instructions.
Step 2: Build line-bot-mcp-server image
Clone this repository:
git clone git@github.com:line/line-bot-mcp-server.gitBuild the Docker image:
docker build -t line/line-bot-mcp-server .Step 3: Configure AI Agent
Please add the following configuration for an AI Agent like Claude Desktop or Cline.
Set the environment variables or arguments as follows:
mcpServers.args: (required) The path toline-bot-mcp-server.CHANNEL_ACCESS_TOKEN: (required) Channel Access Token. You can confirm this by following this instructions.DESTINATION_USER_ID: (optional) The default user ID of the recipient. If the Tool's input does not includeuserId,DESTINATION_USER_IDis required. You can confirm this by following this instructions.
{
"mcpServers": {
"line-bot": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CHANNEL_ACCESS_TOKEN",
"-e",
"DESTINATION_USER_ID",
"line/line-bot-mcp-server"
],
"env": {
"CHANNEL_ACCESS_TOKEN" : "FILL_HERE",
"DESTINATION_USER_ID" : "FILL_HERE"
}
}
}
}Local Development with Inspector
You can use the MCP Inspector to test and debug the server locally.
Prerequisites
Clone the repository:
git clone git@github.com:line/line-bot-mcp-server.git
cd line-bot-mcp-serverInstall dependencies:
npm installBuild the project:
npm run buildRun the Inspector
After building the project, you can start the MCP Inspector:
npx @modelcontextprotocol/inspector node dist/index.js \
-e CHANNEL_ACCESS_TOKEN="YOUR_CHANNEL_ACCESS_TOKEN" \
-e DESTINATION_USER_ID="YOUR_DESTINATION_USER_ID"This will start the MCP Inspector interface where you can interact with the LINE Bot MCP Server tools and test their functionality.
Versioning
This project respects semantic versioning
Contributing
Please check CONTRIBUTING before making a contribution.
Available Tools
12 toolsbroadcast_flex_messageBroadcast Flex MessageADestructive
Broadcast a highly customizable flex message via LINE to all users who have added your LINE Official Account. Supports both bubble (single container) and carousel (multiple swipeable bubbles) layouts. Please be aware that this message will be sent to all users.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark destructiveHint true, so the description's warning ('sent to all users') reinforces this without adding new behavioral insights. The description does not disclose potential side effects like rate limits, quota usage, or message delivery guarantees, but the annotation reduces the burden. It adds some value by describing layout options.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: purpose, layout support, and warning. It is concise, front-loaded with the key action, and each sentence adds distinct value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the extreme complexity of the input schema (nested objects, many optional structures) and no output schema, the description is too brief. It does not cover return values, error handling, or how to construct the message beyond layout types. The agent would need extensive external knowledge to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% for the single parameter 'message', and the description only provides minimal guidance ('Supports bubble and carousel layouts'). It does not explain the structure or common properties of the message object, leaving the agent to parse the complex schema without added semantic help. The description fails to compensate adequately for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool broadcasts a flex message to all LINE Official Account users, with specific verb (broadcast) and resource (flex message). It distinguishes from siblings like push_flex_message by noting 'all users' and from text messages by specifying 'flex message'. The mention of bubble and carousel layouts adds specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states this sends to all users, which clearly distinguishes it from push tools that send to specific users. However, it does not explicitly mention when not to use it (e.g., for targeted messages) or provide alternatives. The warning about sending to all users adds appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
broadcast_text_messageBroadcast Text MessageADestructive
Broadcast a simple text message via LINE to all users who have followed your LINE Official Account. Use this for sending plain text messages without formatting. Please be aware that this message will be sent to all users.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint: true. The description adds meaningful context by explicitly stating the broadcast scope ('to all users who have followed your LINE Official Account') and the warning about sending to all users. This complements the annotation without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each serving a distinct purpose: action definition and behavioral warning. No unnecessary words. Front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking output schema, the tool is simple. The description fully covers what the tool does (broadcast text), how (plain text), and the scope (all followers). No missing critical information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It clarifies that the message is 'plain text' and 'without formatting', adding semantic value beyond the schema's 'const: text' and string constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Broadcast' and the resource 'simple text message via LINE to all users who have followed your LINE Official Account'. It distinguishes from siblings 'broadcast_flex_message' and 'push_text_message' by specifying plain text and broadcast scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this for sending plain text messages without formatting' which implies when to use. It also warns 'this message will be sent to all users', but does not explicitly state when not to use or contrast with alternatives like push_text_message for specific users.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_follower_idsARead-only
Get a list of user IDs of users who have added the LINE Official Account as a friend. This allows you to obtain user IDs for sending messages without manually preparing them.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | The maximum number of user IDs to retrieve in a single request. | |
| start | No | Continuation token to get the next array of user IDs. Returned in the 'next' property of a previous response. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds limited behavioral context. It mentions that the tool obtains user IDs for messaging, which is a benign consequence. No additional details about pagination, rate limits, or other behaviors beyond the read-only nature are disclosed. The description adds minimal value over annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no fluff. The primary action is front-loaded, and the secondary sentence adds context. Every word serves a purpose, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two optional parameters and no output schema. The description explains the result (list of user IDs) and its utility. However, it does not explicitly mention that the response includes a continuation token for pagination, which is a minor gap. Overall, it provides sufficient context for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters (limit and start), so the description does not need to elaborate further. It provides no additional semantic meaning beyond what is already in the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get a list of user IDs of users who have added the LINE Official Account as a friend') and specifies the resource (follower user IDs). It distinguishes this tool from siblings like get_profile (single user) and broadcast/push tools (sending messages). The purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context: obtaining user IDs for sending messages without manual preparation. However, it does not explicitly state when to avoid using this tool or compare with alternatives like get_profile for individual IDs. Guidance is present but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_message_quotaGet Message QuotaARead-only
Get the message quota and consumption of the LINE Official Account. This shows the monthly message limit and current usage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. Description adds context about monthly message limit and current usage, which is valuable beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, clear and front-loaded with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description fully covers the tool's purpose for a simple read-only operation with no parameters and no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist in the schema; description adds no parameter details, but baseline is 4 for 0-parameter tools with 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'message quota and consumption'. It distinguishes from sibling tools that are about sending messages or managing rich menus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking quota before sending messages, but does not explicitly state when to use this tool over siblings or provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_profileGet ProfileARead-only
Get detailed profile information of a LINE user including display name, profile picture URL, status message and language.
| Name | Required | Description | Default |
|---|---|---|---|
| userId | No | The user ID to get a profile. Defaults to DESTINATION_USER_ID. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true. Description adds value by specifying what data is returned (display name, profile picture URL, etc.), which is behavioral beyond the annotation. No contradictory information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with purpose, no extraneous words. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity (1 optional parameter, no output schema), the description adequately covers what the tool does and what it returns. Minor gap: no mention of error handling or access requirements, but acceptable for a read-only tool with annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the schema already fully describes the 'userId' parameter with default and description). The tool description does not provide additional parameter semantics beyond what the schema offers, hence baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'get' and resource 'detailed profile information of a LINE user', listing specific fields (display name, profile picture URL, status message, language). It distinguishes from sibling tools which are about messaging and rich menu management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: retrieving a user's profile. No explicit when-not-to-use or alternatives, but context from sibling tool names suggests this is the only tool for fetching individual profile data, making usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
push_flex_messagePush Flex MessageCDestructive
Push a highly customizable flex message to a user via LINE. Supports both bubble (single container) and carousel (multiple swipeable bubbles) layouts.
| Name | Required | Description | Default |
|---|---|---|---|
| userId | No | The user ID to receive a message. Defaults to DESTINATION_USER_ID. | |
| message | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate destructiveHint=true, so the description should add behavioral context beyond mutation. It mentions high customizability and layout types, but omits important details like rate limits, recipient requirements, or validation errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no superfluous information. The description is front-loaded with the primary action and key distinguishing feature (layout types).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's complexity (large nested schema), the description is very brief. It omits critical information like required altText, recipient constraints, error handling, and references to official documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%. The description adds value by explaining the two layout types (bubble and carousel), which helps understand the nested message.contents structure. The userId parameter is already well-documented in the schema. Baseline 3 with partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'push' and resource 'flex message', and specifies two layout types (bubble and carousel). However, it does not explicitly differentiate from sibling tools like push_text_message or broadcast_flex_message, but the distinction is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., push_text_message for simple text, broadcast_flex_message for broadcasting). No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
push_text_messagePush Text MessageADestructive
Push a simple text message to a user via LINE. Use this for sending plain text messages without formatting.
| Name | Required | Description | Default |
|---|---|---|---|
| userId | No | The user ID to receive a message. Defaults to DESTINATION_USER_ID. | |
| message | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide destructiveHint=true, so description carries lower burden. Description adds minimal extra context beyond that it pushes a message. Does not mention potential side effects (e.g., LINE API restrictions, user must be a friend) or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, first sentence dedicated to purpose, second to usage. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has simple parameters and no output schema. Description adequately covers purpose and basic usage but lacks error conditions, prerequisites (e.g., user must be a LINE friend), or integration details. Sufficient for a simple tool but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (only message parameter has description). Description mentions 'simple text message' and 'plain text', which relates to message but does not explain the nested structure or userId parameter beyond what schema provides. Lacks compensation for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Push' and resource 'text message to a user via LINE', distinguishing it from sibling tools like broadcast (sends to all) and flex (formatted message) by specifying 'plain text without formatting'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence explicitly states when to use this tool ('for sending plain text messages without formatting'), implying it is not for formatted messages. However, it does not explicitly state when not to use it (e.g., for broadcasting) or provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
12 tool updates
v0.0.1-local- First observed
broadcast_flex_message - First observed
broadcast_text_message - First observed
cancel_rich_menu_default - First observed
create_rich_menu - First observed
delete_rich_menu - First observed
get_follower_ids - First observed
get_message_quota - First observed
get_profile - First observed
get_rich_menu_list - First observed
push_flex_message - First observed
push_text_message - First observed
set_rich_menu_default
TDQS
Each tool targets a distinct action and resource: broadcast vs push, text vs flex, rich menu management (create, delete, set, cancel, list), and informational (get follower IDs, quota, profile). No two tools have overlapping purposes.
All tools follow a consistent verb_noun pattern using snake_case (e.g., broadcast_flex_message, create_rich_menu, get_profile). No mixing of conventions.
With 12 tools, the server is well-scoped, covering essential LINE Bot operations without unnecessary bloat. The count falls comfortably within the ideal 3-15 range.
The tool set covers core messaging (broadcast/push, text/flex), rich menu lifecycle (create, delete, list, default), and user/account info (followers, profile, quota). Minor gaps like replying to messages or sending media types are absent, but the server is sufficiently functional for its intended use.
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