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MCP Headless Gmail Server

by baryhuang
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Python
Remote

MCP Headless Gmail Server (NPM & Docker)

npm version Docker Pulls License: MIT

A MCP (Model Context Protocol) server that provides get, send Gmails without local credential or token setup.

Why MCP Headless Gmail Server?

Critical Advantages

  • Headless & Remote Operation: Unlike other MCP Gmail solutions that require running outside of docker and local file access, this server can run completely headless in remote environments with no browser no local file access.

  • Decoupled Architecture: Any client can complete the OAuth flow independently, then pass credentials as context to this MCP server, creating a complete separation between credential storage and server implementation.

Nice but not critical

  • Focused Functionality: In many use cases, especially for marketing applications, only Gmail access is needed without additional Google services like Calendar, making this focused implementation ideal.

  • Docker-Ready: Designed with containerization in mind for a well-isolated, environment-independent, one-click setup.

  • Reliable Dependencies: Built on the well-maintained google-api-python-client library.

Related MCP server: MCP Headless Gmail Server

Features

  • Get most recent emails from Gmail with the first 1k characters of the body

  • Get full email body content in 1k chunks using offset parameter

  • Send emails through Gmail

  • Refresh access tokens separately

  • Automatic refresh token handling

Prerequisites

  • Python 3.10 or higher

  • Google API credentials (client ID, client secret, access token, and refresh token)

Installation

# Clone the repository
git clone https://github.com/baryhuang/mcp-headless-gmail.git
cd mcp-headless-gmail

# Install dependencies
pip install -e .

Docker

Building the Docker Image

# Build the Docker image
docker build -t mcp-headless-gmail .

Usage with Claude Desktop

You can configure Claude Desktop to use the Docker image by adding the following to your Claude configuration:

docker

{
  "mcpServers": {
    "gmail": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "buryhuang/mcp-headless-gmail:latest"
      ]
    }
  }
}

npm version

{
  "mcpServers": {
    "gmail": {
      "command": "npx",
      "args": [
        "@peakmojo/mcp-server-headless-gmail"
      ]
    }
  }
}

Note: With this configuration, you'll need to provide your Google API credentials in the tool calls as shown in the Using the Tools section. Gmail credentials are not passed as environment variables to maintain separation between credential storage and server implementation.

Cross-Platform Publishing

To publish the Docker image for multiple platforms, you can use the docker buildx command. Follow these steps:

  1. Create a new builder instance (if you haven't already):

    docker buildx create --use

  2. Build and push the image for multiple platforms:

    docker buildx build --platform linux/amd64,linux/arm64,linux/arm/v7 -t buryhuang/mcp-headless-gmail:latest --push .

  3. Verify the image is available for the specified platforms:

    docker buildx imagetools inspect buryhuang/mcp-headless-gmail:latest

Usage

The server provides Gmail functionality through MCP tools. Authentication handling is simplified with a dedicated token refresh tool.

Starting the Server

mcp-server-headless-gmail

Using the Tools

When using an MCP client like Claude, you have two main ways to handle authentication:

Refreshing Tokens (First Step or When Tokens Expire)

If you have both access and refresh tokens:

{
  "google_access_token": "your_access_token",
  "google_refresh_token": "your_refresh_token",
  "google_client_id": "your_client_id",
  "google_client_secret": "your_client_secret"
}

If your access token has expired, you can refresh with just the refresh token:

{
  "google_refresh_token": "your_refresh_token",
  "google_client_id": "your_client_id",
  "google_client_secret": "your_client_secret"
}

This will return a new access token and its expiration time, which you can use for subsequent calls.

Getting Recent Emails

Retrieves recent emails with the first 1k characters of each email body:

{
  "google_access_token": "your_access_token",
  "max_results": 5,
  "unread_only": false
}

Response includes:

  • Email metadata (id, threadId, from, to, subject, date, etc.)

  • First 1000 characters of the email body

  • body_size_bytes: Total size of the email body in bytes

  • contains_full_body: Boolean indicating if the entire body is included (true) or truncated (false)

Getting Full Email Body Content

For emails with bodies larger than 1k characters, you can retrieve the full content in chunks:

{
  "google_access_token": "your_access_token",
  "message_id": "message_id_from_get_recent_emails",
  "offset": 0
}

You can also get email content by thread ID:

{
  "google_access_token": "your_access_token",
  "thread_id": "thread_id_from_get_recent_emails",
  "offset": 1000
}

The response includes:

  • A 1k chunk of the email body starting from the specified offset

  • body_size_bytes: Total size of the email body

  • chunk_size: Size of the returned chunk

  • contains_full_body: Boolean indicating if the chunk contains the remainder of the body

To retrieve the entire email body of a long message, make sequential calls increasing the offset by 1000 each time until contains_full_body is true.

Sending an Email

{
  "google_access_token": "your_access_token",
  "to": "recipient@example.com",
  "subject": "Hello from MCP Gmail",
  "body": "This is a test email sent via MCP Gmail server",
  "html_body": "<p>This is a <strong>test email</strong> sent via MCP Gmail server</p>"
}

Token Refresh Workflow

  1. Start by calling the gmail_refresh_token tool with either:

    • Your full credentials (access token, refresh token, client ID, and client secret), or

    • Just your refresh token, client ID, and client secret if the access token has expired

  2. Use the returned new access token for subsequent API calls.

  3. If you get a response indicating token expiration, call the gmail_refresh_token tool again to get a new token.

This approach simplifies most API calls by not requiring client credentials for every operation, while still enabling token refresh when needed.

Obtaining Google API Credentials

To obtain the required Google API credentials, follow these steps:

  1. Go to the Google Cloud Console

  2. Create a new project

  3. Enable the Gmail API

  4. Configure OAuth consent screen

  5. Create OAuth client ID credentials (select "Desktop app" as the application type)

  6. Save the client ID and client secret

  7. Use OAuth 2.0 to obtain access and refresh tokens with the following scopes:

    • https://www.googleapis.com/auth/gmail.readonly (for reading emails)

    • https://www.googleapis.com/auth/gmail.send (for sending emails)

Token Refreshing

This server implements automatic token refreshing. When your access token expires, the Google API client will use the refresh token, client ID, and client secret to obtain a new access token without requiring user intervention.

Security Note

This server requires direct access to your Google API credentials. Always keep your tokens and credentials secure and never share them with untrusted parties.

License

See the LICENSE file for details.

Available Tools

4 tools
gmail_get_email_body_chunkB

Get a 1k character chunk of an email body starting from the specified offset

ParametersJSON Schema
NameRequiredDescriptionDefault
google_access_tokenYesGoogle OAuth2 access token
message_idNoID of the message to retrieve
thread_idNoID of the thread to retrieve (will get the first message if multiple exist)
offsetNoOffset in characters to start from (default: 0)

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the 1k character chunking behavior, which is valuable, but doesn't address authentication needs (though implied by google_access_token parameter), error handling, rate limits, or what happens with invalid offsets/message_ids. For a tool with no annotation coverage, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that immediately conveys the core functionality without any wasted words. It's appropriately sized and front-loaded with the essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It explains the chunking behavior but lacks details about authentication requirements, error conditions, and how this tool relates to siblings. Without annotations or output schema, more behavioral context would be helpful for safe usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds context about the 'offset' parameter (default: 0) and clarifies that thread_id retrieves the first message if multiple exist, providing some value beyond the schema. However, it doesn't explain parameter interactions or provide additional semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get'), resource ('email body chunk'), and key constraint ('1k character chunk starting from specified offset'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like gmail_get_recent_emails, which retrieves multiple emails rather than a specific body chunk.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites (like needing a message_id or thread_id), nor does it explain when this tool is appropriate compared to gmail_get_recent_emails for retrieving email content.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

gmail_get_recent_emailsC

Get the most recent emails from Gmail (returns metadata, snippets, and first 1k chars of body)

ParametersJSON Schema
NameRequiredDescriptionDefault
google_access_tokenYesGoogle OAuth2 access token
max_resultsNoMaximum number of emails to return (default: 10)
unread_onlyNoWhether to return only unread emails (default: False)

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions what data is returned (metadata, snippets, first 1k chars of body) which is helpful, but doesn't cover important behavioral aspects like authentication requirements (beyond the parameter), rate limits, pagination behavior, error conditions, or whether this is a read-only operation. For a tool with no annotations, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that communicates the core functionality and return format. It's appropriately sized for a straightforward retrieval tool, though it could potentially benefit from slightly more detail given the lack of annotations and output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of email retrieval (3 parameters, no annotations, no output schema), the description is insufficiently complete. It doesn't explain the return format in detail, doesn't mention authentication requirements beyond the parameter, and doesn't cover important behavioral aspects. For a tool with no annotations or output schema, the description should provide more context about what to expect from the operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does all the parameter documentation work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get the most recent emails from Gmail' specifies the verb (get) and resource (emails). It distinguishes from sibling 'gmail_get_email_body_chunk' by indicating it returns metadata, snippets, and partial body content, but doesn't explicitly differentiate from other siblings like 'gmail_send_email' or 'gmail_refresh_token' beyond the obvious functional difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives is provided. The description doesn't mention when to use this versus 'gmail_get_email_body_chunk' for full body retrieval, or when to use 'gmail_refresh_token' for token management. Usage context is implied by the tool name but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

gmail_refresh_tokenB

Refresh the access token using the refresh token and client credentials

ParametersJSON Schema
NameRequiredDescriptionDefault
google_access_tokenNoGoogle OAuth2 access token (optional if expired)
google_refresh_tokenYesGoogle OAuth2 refresh token
google_client_idYesGoogle OAuth2 client ID for token refresh
google_client_secretYesGoogle OAuth2 client secret for token refresh

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states what the tool does at a high level. It doesn't disclose behavioral traits like whether this invalidates previous tokens, rate limits, error conditions, or what the refreshed token enables. For a security-sensitive operation with zero annotation coverage, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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 with zero waste. It's appropriately sized and front-loaded, with every word contributing to understanding the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a security-critical token refresh operation with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after refresh (e.g., token lifetime, scope preservation), error handling, or integration with sibling tools. Given the complexity and lack of structured data, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds no parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain relationships between parameters or provide usage examples). Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Refresh') and resource ('access token'), specifying it uses refresh token and client credentials. It distinguishes from sibling tools (email-related operations) by focusing on authentication token management, though it doesn't explicitly name alternatives for token refresh.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when access tokens expire (via 'optional if expired' in schema), but doesn't explicitly state when to use this tool versus alternatives like initial authentication or other token management methods. No guidance on prerequisites or exclusions is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

gmail_send_emailC

Send an email via Gmail

ParametersJSON Schema
NameRequiredDescriptionDefault
google_access_tokenYesGoogle OAuth2 access token
toYesRecipient email address
subjectYesEmail subject
bodyYesEmail body content (plain text)
html_bodyNoEmail body content in HTML format (optional)

TDQS

C2.9/5.0
Behavior2/5

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 action ('send an email') but lacks critical details: it doesn't mention authentication requirements (implied by the 'google_access_token' parameter but not explicitly stated), potential rate limits, error handling, or what happens upon success (e.g., whether it returns a confirmation). This leaves significant gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words—'Send an email via Gmail' is front-loaded and directly conveys the core action. It's appropriately sized for the tool's complexity, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a mutation tool with 5 parameters, no annotations, and no output schema), the description is incomplete. It fails to address key contextual aspects like authentication needs, behavioral traits (e.g., what 'send' entails operationally), or output expectations, leaving the agent with insufficient information for reliable use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with all parameters well-documented in the schema (e.g., 'to' as recipient email, 'body' as plain text content). The description adds no additional meaning beyond the schema, such as explaining parameter interactions (e.g., 'body' vs. 'html_body') or constraints. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Send an email via Gmail' clearly states the verb ('send') and resource ('email via Gmail'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'gmail_get_recent_emails' or 'gmail_refresh_token' beyond the obvious action distinction, which keeps it from a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing authentication via 'google_access_token'), nor does it clarify scenarios where other tools like 'gmail_get_recent_emails' might be more appropriate, leaving usage context entirely implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: retrieving email body chunks, listing recent emails, refreshing tokens, and sending emails. There is no overlap in functionality that would cause confusion or misselection.

Naming Consistency5/5

All tools follow a consistent 'gmail_verb_noun' pattern with snake_case, making them predictable and easy to understand. The naming convention is uniform across all four tools.

Tool Count4/5

With 4 tools, the count is reasonable for a Gmail server, though it feels slightly thin for covering all common email operations. It includes core functions but could benefit from additional tools like searching or managing drafts.

Completeness3/5

The tools cover basic email operations (read, list, send) and authentication, but there are notable gaps such as searching emails, managing labels, or handling attachments. This could limit agents in performing more complex email tasks.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

Resources

Unclaimed servers have limited discoverability.

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