The Authenticator App MCP Server enables AI agents to securely retrieve authentication credentials for automated login processes. It provides three key functions:
Retrieve 2FA codes for specific website/username combinations
Fetch passwords for specific website/username combinations
Obtain lists of accounts available for login to specific websites
Supports the Debian version of Authenticator App · 2FA through .deb package installation, enabling AI agents to retrieve secure authentication credentials.
Supports the desktop version of Authenticator App · 2FA on Linux platforms, enabling AI agents to access authentication credentials securely.
Supports the desktop version of Authenticator App · 2FA on macOS, allowing AI agents to securely retrieve 2FA codes and passwords for automated login processes.
Provides compatibility with the Ubuntu/Debian version of Authenticator App · 2FA through .deb package installation, allowing secure access to authentication credentials.
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., "@Authenticator App MCP Server get my 2FA code for GitHub"
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.
A secure MCP (Model Context Protocol) server that enables AI agents to interact with the Authenticator App. It provides seamless access to 2FA codes and passwords, allowing AI agents to assist with automated login processes while maintaining security. This tool bridges the gap between AI assistants and secure authentication, making it easier to manage your credentials across different platforms and websites.
Open your AI agent's integrated chat interface (such as Cursor's agent mode).
Ask AI agent to retrieve your 2FA code or password for your desired website and account.
AI agent will securely fetch these credentials, then can utilize them to automate your login process.
This MCP server is specifically designed for use with Authenticator App · 2FA.
Related MCP server: ssh-mcp-server
Many AI clients use a configuration file to manage MCP servers.
The authenticator-mcp tool can be configured by adding the following to your configuration file.
NOTE: You will need to create a Authenticator App access token to use this server. Instructions on how to create a Authenticator App access token can be found here.
{
"mcpServers": {
"Authenticator App MCP": {
"command": "npx",
"args": ["-y", "authenticator-mcp", "--access-token=YOUR-KEY"]
}
}
}{
"mcpServers": {
"Authenticator App MCP": {
"command": "cmd",
"args": ["/c", "npx", "-y", "authenticator-mcp", "--access-token=YOUR-KEY"]
}
}
}Or you can set AUTHENTICATOR_ACCESS_TOKEN in the env field.
Launch the desktop version of Authenticator App · 2FA.
Navigate to Settings and locate the MCP Server section.
Enable the MCP Server by toggling it ON, then proceed to generate your access token.
Please note that the access token will only be displayed once. Be sure to copy it immediately and add it to your MCP client configuration.
Retrieve the current 2FA code for a username when logging into a website.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | The username or email of the account you need to login, e.g. "john.doe@example.com" | |
| website | Yes | The domain name of the website you need to login, e.g. "github.com" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves a 2FA code, implying a read operation, but lacks details on security implications, rate limits, authentication requirements, or response format. This is a significant gap for a tool handling sensitive data.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand quickly.
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?
For a tool handling sensitive 2FA codes with no annotations and no output schema, the description is incomplete. It lacks critical details like security constraints, error handling, or return value format, leaving gaps in understanding how to use it effectively in context.
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%, so the schema fully documents both parameters (username and website). The description adds minimal value beyond the schema, as it only implies the parameters are used for login context without providing additional syntax or format details.
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 ('Retrieve') and resource ('current 2FA code for a username'), specifying the context ('when logging into a website'). It distinguishes from sibling tools like get_account_list (lists accounts) and get_password (retrieves passwords), though it doesn't explicitly name them for comparison.
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 mentions 'when logging into a website,' which provides some context, but it doesn't offer explicit guidance on when to use this tool versus alternatives like get_password for non-2FA logins or prerequisites. No exclusions or detailed scenarios are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve the accounts can be used when logging into a website.
| Name | Required | Description | Default |
|---|---|---|---|
| website | Yes | The domain name of the website you need to login, e.g. "github.com" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves accounts, implying a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, data sensitivity, or what 'accounts' entails (e.g., usernames, emails). This leaves key behavioral traits unspecified for a tool handling login-related data.
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 a single, straightforward sentence that efficiently conveys the core purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more structured by front-loading key details more explicitly. There's minimal waste, earning a high score for conciseness.
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 tool's low complexity (1 parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose but lacks details on behavioral aspects like security or usage guidelines. Without annotations or output schema, the description should do more to compensate, but it provides a minimal viable explanation, scoring at the threshold of adequacy.
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, with the 'website' parameter fully documented as 'The domain name of the website you need to login, e.g. "github.com".' The description adds no additional parameter semantics beyond this, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for gaps.
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's purpose: 'Retrieve the accounts can be used when logging into a website.' It specifies the action ('retrieve') and resource ('accounts'), and the context ('when logging into a website') is clear. However, it doesn't explicitly differentiate from sibling tools like get_2fa_code or get_password, which prevents a score of 5.
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 provides minimal guidance by mentioning 'when logging into a website,' which implies usage context but lacks explicit when-to-use rules or alternatives. There's no mention of when to use this tool versus get_2fa_code or get_password, or any prerequisites or exclusions, leaving significant gaps in usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve the password for a username when logging into a website.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | The username or email of the account you need to login, e.g. "john.doe@example.com" | |
| website | Yes | The domain name of the website you need to login, e.g. "github.com" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves a password, implying a read operation, but doesn't cover critical aspects such as authentication requirements, security implications (e.g., if it's stored securely), rate limits, or what happens on failure (e.g., if the password isn't found). This leaves significant gaps for a tool handling sensitive data.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly while conveying the essential 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?
Given the complexity of handling passwords (sensitive data) and the lack of annotations and output schema, the description is incomplete. It doesn't address security behaviors, error handling, or return values, which are crucial for such a tool. The description alone is insufficient for safe and effective use by an AI agent.
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, with clear documentation for both parameters ('username' and 'website'), including examples. The description adds no additional parameter semantics beyond what the schema provides, such as format details or constraints. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.
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's purpose with a specific verb ('Retrieve') and resource ('password for a username'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_2fa_code' or 'get_account_list', which would require mentioning it's specifically for password retrieval rather than other authentication data or account listings.
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 provides a basic context ('when logging into a website'), but it lacks explicit guidance on when to use this tool versus alternatives like 'get_2fa_code' for two-factor codes or 'get_account_list' for listing accounts. There's no mention of prerequisites, exclusions, or specific scenarios, leaving usage unclear relative to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0get_2fa_codeget_account_listget_passwordEach tool has a clearly distinct purpose: get_2fa_code retrieves time-based codes, get_account_list lists available accounts, and get_password retrieves passwords. There is no overlap in functionality, making tool selection unambiguous for an agent.
All tool names follow a consistent verb_noun pattern with 'get_' prefix (get_2fa_code, get_account_list, get_password). The naming is uniform and predictable, using snake_case throughout without any deviations.
With only 3 tools, the server feels thin for an authenticator app domain that might benefit from operations like adding/removing accounts or updating credentials. While the tools cover core retrieval needs, the count is borderline minimal for comprehensive functionality.
The toolset is severely incomplete for an authenticator app, lacking any write operations such as adding accounts, updating passwords, or managing 2FA settings. Agents can only retrieve data, leading to dead ends for common workflows like account setup or credential changes.
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