What can mcp-headless-gmail do?

headless-gmail-message-retrieval-with-pagination, chunked-email-body-retrieval-with-streaming, runtime-credential-injection-with-oauth-token-management, email-composition-and-sending-with-mime-construction, mcp-protocol-integration-for-llm-agent-orchestration, automatic-token-refresh-with-expiration-handling

mcp-headless-gmail

MCP ServerFree

Read recent Gmail messages, retrieve full bodies in chunks, and send emails. Operate headlessly with runtime-provided credentials to avoid local setup. Automatically refresh tokens to keep workflows uninterrupted.

Open Source

/ 100

6 capabilities

Capabilities6 decomposed

headless-gmail-message-retrieval-with-pagination

Medium confidence

Fetches recent Gmail messages via the Gmail API without requiring local browser automation or UI interaction. Implements pagination through message list queries to retrieve metadata (sender, subject, timestamp, message ID) in batches, enabling LLM agents to discover and iterate over inbox contents programmatically. Uses Gmail API's labelIds and maxResults parameters to filter and limit result sets.

Solves for

I need my AI agent to read recent emails from my inbox without opening Gmail in a browserI want to paginate through Gmail messages to find specific conversations or sendersI need to retrieve email metadata (subject, from, date) to make decisions about which emails to process next

Best for

AI agents and LLM-based workflows that need email awareness

headless server environments without UI capabilities

teams building email-triggered automation pipelines

Requires

Gmail API credentials (OAuth 2.0 client ID or service account)

Google Cloud Project with Gmail API enabled

Valid refresh token or access token passed at runtime

Limitations

Retrieves only recent messages — no full-text search across entire mailbox history

Pagination limited by Gmail API rate limits (typically 1000 requests/user/100 seconds)

Message list queries return metadata only; full body retrieval requires separate API calls per message

What makes it unique

Operates entirely headless without Selenium or browser automation, using direct Gmail API calls with runtime-injected credentials, eliminating local setup overhead and enabling deployment in containerized/serverless environments

vs alternatives

Avoids browser automation overhead (Selenium, Puppeteer) that adds latency and resource consumption; direct API access is faster and more reliable for agent-driven workflows than UI scraping

chunked-email-body-retrieval-with-streaming

Medium confidence

Retrieves the full MIME body of a Gmail message and parses it into structured chunks (plain text, HTML, attachments metadata) via the Gmail API's messages.get endpoint with format=full. Implements chunking logic to break large email bodies into manageable pieces for LLM context windows, preventing token overflow when processing lengthy emails. Handles multipart MIME structures to extract text/plain and text/html parts separately.

Solves for

I need to read the complete body of an email, not just the snippet previewI want to process long emails by breaking them into chunks that fit my LLM's context windowI need to extract both plain text and HTML versions of email bodies for different downstream uses

Best for

LLM agents that need to understand full email content for decision-making

workflows processing emails with large attachments or complex MIME structures

systems with strict token budgets that require intelligent chunking

Requires

Gmail API credentials with message read scope

Valid access token with gmail.readonly or gmail.modify permission

Message ID from prior message list retrieval

Limitations

Chunking strategy not specified in repository — likely naive line-based or character-based splitting rather than semantic chunking

Attachment bodies are not fully retrieved — only metadata (filename, MIME type) is extracted

Large emails (>25MB) may hit Gmail API payload limits; no built-in streaming or resumable download

What makes it unique

Implements automatic chunking of email bodies to fit LLM context windows, handling MIME multipart structures natively rather than treating emails as opaque blobs

vs alternatives

More context-aware than naive email clients that load entire messages into memory; chunking prevents LLM token overflow without requiring manual email truncation by users

runtime-credential-injection-with-oauth-token-management

Medium confidence

Accepts Gmail OAuth 2.0 credentials (access token, refresh token, client ID, client secret) at runtime rather than requiring local .env files or hardcoded secrets. Implements automatic token refresh logic using the Gmail API's OAuth 2.0 refresh flow, detecting token expiration and silently obtaining new access tokens without interrupting agent workflows. Credentials are passed as MCP server parameters or environment variables at startup, enabling secure deployment in containerized and serverless environments.

Solves for

I want to deploy this Gmail integration in a Docker container without baking secrets into the imageI need my email agent to keep working even if the access token expires mid-workflowI want to pass different Gmail credentials for different users without restarting the server

Best for

teams deploying MCP servers in containerized/Kubernetes environments

multi-tenant SaaS platforms that need per-user Gmail access

CI/CD pipelines and serverless functions that inject secrets at runtime

Requires

Valid Gmail OAuth 2.0 refresh token (obtained via prior authorization)

Google Cloud Project with OAuth 2.0 credentials (client ID, client secret)

Environment variables or MCP parameter injection mechanism

Limitations

Refresh token must be obtained out-of-band via OAuth 2.0 consent flow — MCP server does not implement the full OAuth flow

No built-in credential rotation or expiration monitoring — relies on Gmail API to reject expired tokens

Credentials stored in memory only — no persistence across server restarts; requires re-injection on each startup

What makes it unique

Eliminates local credential setup by accepting OAuth tokens at runtime, with automatic refresh logic that keeps workflows uninterrupted across token expiration boundaries

vs alternatives

More secure than hardcoded credentials or local .env files; enables containerized deployment without baking secrets into images, unlike traditional Gmail client libraries that require local authentication flows

email-composition-and-sending-with-mime-construction

Medium confidence

Constructs and sends emails via the Gmail API's messages.send endpoint by building RFC 5322-compliant MIME messages programmatically. Accepts recipient addresses, subject, body (plain text and/or HTML), and optional attachments as structured input, then encodes them into base64-encoded MIME format required by Gmail API. Handles multipart message construction (text/plain + text/html alternatives, attachments as separate parts) without requiring external SMTP libraries.

Solves for

I want my AI agent to send emails in response to events or user requestsI need to compose emails with both plain text and HTML versions for better client compatibilityI want to send emails with attachments programmatically from my agent

Best for

LLM agents that need to take action by sending emails

automation workflows triggered by email events

systems that generate email responses dynamically based on AI reasoning

Requires

Gmail API credentials with gmail.send or gmail.modify scope

Valid access token with send permission

Recipient email address(es)

Limitations

Attachment support not explicitly documented — likely limited to small files (<25MB per Gmail API limits)

No built-in email template engine — requires pre-formatting of HTML bodies

No scheduling support — emails are sent immediately; no draft creation or delayed send

What makes it unique

Constructs MIME messages natively without external SMTP libraries, enabling email sending directly through Gmail API with automatic multipart handling for text/HTML alternatives and attachments

vs alternatives

Avoids SMTP server setup and configuration; uses Gmail's infrastructure directly, making it suitable for agents that need reliable email sending without managing mail server credentials or dealing with spam filtering

mcp-protocol-integration-for-llm-agent-orchestration

Medium confidence

Implements the Model Context Protocol (MCP) server specification, exposing Gmail capabilities as callable tools that LLM agents can invoke through a standardized interface. Defines MCP tools with JSON schemas for each Gmail operation (list messages, get body, send email), enabling Claude, other LLMs, and agentic frameworks to discover and call Gmail functions without custom integration code. Handles MCP request/response serialization and error propagation back to the agent.

Solves for

I want Claude or another LLM to be able to read and send emails as part of an agentic workflowI need a standardized way to expose Gmail capabilities to multiple LLM models without rewriting integration codeI want my agent to discover available email operations and their parameters automatically

Best for

teams building multi-tool AI agents with Claude or other LLMs

frameworks implementing MCP client support (e.g., Claude Desktop, custom agent runtimes)

organizations standardizing on MCP for tool integration across multiple services

Requires

MCP client implementation (Claude Desktop, custom agent framework, or MCP SDK)

Node.js runtime (likely — language not specified in repo)

MCP server configuration file or environment setup

Limitations

MCP protocol overhead adds latency (~50-100ms per tool call) compared to direct API calls

Tool schemas must be manually defined and kept in sync with implementation — no automatic schema generation

Error handling depends on MCP client implementation — some clients may not properly propagate Gmail API errors

What makes it unique

Exposes Gmail operations as MCP tools, enabling standardized integration with any LLM or agent framework that supports MCP, rather than requiring custom SDK bindings for each model

vs alternatives

MCP abstraction allows the same Gmail server to work with Claude, GPT-4, open-source LLMs, and custom agents without code changes; more flexible than model-specific plugins or SDKs

automatic-token-refresh-with-expiration-handling

Medium confidence

Monitors access token expiration and automatically invokes the Gmail OAuth 2.0 refresh endpoint to obtain new tokens before they expire or when API calls fail with 401 Unauthorized. Implements retry logic that catches token expiration errors, refreshes the token silently, and retries the original request without exposing token management complexity to the agent. Maintains refresh token securely in memory and uses it to generate new access tokens as needed.

Solves for

I want my email agent to keep working for hours or days without manual token refreshI need transparent token management so my agent doesn't have to handle expiration errorsI want to avoid interrupting long-running workflows due to token expiration

Best for

long-running agents that process emails over extended periods

unattended automation workflows that cannot prompt for re-authentication

systems that need high availability and minimal manual intervention

Requires

Valid Gmail OAuth 2.0 refresh token

Google Cloud Project OAuth 2.0 credentials (client ID, client secret)

Network connectivity to Google's OAuth 2.0 token endpoint

Limitations

Refresh token itself does not expire in Gmail's standard implementation, but may be revoked by user — no handling for revocation detection

Token refresh adds latency (~500ms-1s) when triggered; no proactive refresh before expiration to avoid this latency

No metrics or logging for token refresh events — difficult to debug token-related issues in production

What makes it unique

Implements automatic token refresh with retry logic, allowing agents to operate continuously without manual re-authentication or explicit token management code

vs alternatives

More resilient than manual token refresh or static access tokens; prevents workflow interruptions due to token expiration, unlike basic Gmail client libraries that require explicit re-authentication

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with mcp-headless-gmail, ranked by overlap. Discovered automatically through the match graph.

MCP Server41

@gongrzhe/server-gmail-autoauth-mcp

Gmail MCP server with auto authentication support

oauth2 auto-authentication for gmail apigmail message retrieval and filteringpersistent token storage and refresh lifecyclegmail thread and conversation retrieval

4 shared capabilities

MCP Server37

@gongrzhe/server-gmail-autoauth-mcp

Gmail MCP server with auto authentication support

oauth2 auto-authentication for gmail api accessautomatic token refresh and credential lifecycle managementgmail message retrieval via mcp tools

3 shared capabilities

MCP Server25

@cardor/email-management

A Node.js application for managing email workflows using the ModelContextProtocol (MCP).

email authentication and credential management

1 shared capability

MCP Server30

Gmail MCP Server

Enable AI applications to securely send and manage emails through Gmail with multi-user OAuth2 authentication. Compose, send, and manage drafts with HTML and plain text support while keeping credentials and tokens encrypted and server-side. Seamlessly integrate with MCP clients like Claude Desktop f

secure multi-user oauth2 email authentication

1 shared capability

MCP Server30

Gmail Email Management Server

Manage your Gmail emails, threads, labels, drafts, and settings through a standardized interface. Send, draft, and organize emails efficiently with full Gmail API coverage. Securely authenticate using OAuth2 for seamless mailbox operations.

secure authentication via oauth2

1 shared capability

MCP Server26

MailSandbox

** - MailSandbox (a fork of Mailpit) is a fast, zero-dependency email testing tool & API with a web UI, SMTP server, Postmark API emulation, and MCP server for AI-assisted debugging.

smtp server with email interception and storage

1 shared capability

Best For

✓AI agents and LLM-based workflows that need email awareness
✓headless server environments without UI capabilities
✓teams building email-triggered automation pipelines
✓LLM agents that need to understand full email content for decision-making
✓workflows processing emails with large attachments or complex MIME structures
✓systems with strict token budgets that require intelligent chunking
✓teams deploying MCP servers in containerized/Kubernetes environments
✓multi-tenant SaaS platforms that need per-user Gmail access

Known Limitations

⚠Retrieves only recent messages — no full-text search across entire mailbox history
⚠Pagination limited by Gmail API rate limits (typically 1000 requests/user/100 seconds)
⚠Message list queries return metadata only; full body retrieval requires separate API calls per message
⚠Chunking strategy not specified in repository — likely naive line-based or character-based splitting rather than semantic chunking
⚠Attachment bodies are not fully retrieved — only metadata (filename, MIME type) is extracted
⚠Large emails (>25MB) may hit Gmail API payload limits; no built-in streaming or resumable download

Requirements

Gmail API credentials (OAuth 2.0 client ID or service account)Google Cloud Project with Gmail API enabledValid refresh token or access token passed at runtimeGmail API credentials with message read scopeValid access token with gmail.readonly or gmail.modify permissionMessage ID from prior message list retrievalValid Gmail OAuth 2.0 refresh token (obtained via prior authorization)Google Cloud Project with OAuth 2.0 credentials (client ID, client secret)

Input / Output

Accepts: query parameters (labelIds, maxResults, pageToken), OAuth 2.0 access token, message ID (string), chunk size parameter (optional, integer), format preference (plain text or HTML), environment variables: GMAIL_ACCESS_TOKEN, GMAIL_REFRESH_TOKEN, GMAIL_CLIENT_ID, GMAIL_CLIENT_SECRET, MCP server initialization parameters, JSON object with to (string or array), subject (string), body (string), htmlBody (optional string), attachments (optional array), MCP tool call requests with JSON parameters, implicit — automatic based on token expiration

Produces: JSON array of message objects with id, threadId, labelIds, snippet, internalDate, JSON object with chunks array, each containing text content, MIME type, and sequence number, implicit — no direct output; enables all other Gmail API capabilities, JSON object with messageId and threadId from Gmail API response, MCP tool result responses with JSON data or error objects, implicit — returns new access token for use in subsequent API calls

UnfragileRank

Adoption5%(25% weight)

Quality27%(25% weight)

Ecosystem62%(15% weight)

Match Graph25%(30% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

6 capabilities

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Capabilities6 decomposed

headless-gmail-message-retrieval-with-pagination

Medium confidence

Solves for

Best for

AI agents and LLM-based workflows that need email awareness

headless server environments without UI capabilities

teams building email-triggered automation pipelines

Requires

Gmail API credentials (OAuth 2.0 client ID or service account)

Google Cloud Project with Gmail API enabled

Valid refresh token or access token passed at runtime

Limitations

Retrieves only recent messages — no full-text search across entire mailbox history

Pagination limited by Gmail API rate limits (typically 1000 requests/user/100 seconds)

Message list queries return metadata only; full body retrieval requires separate API calls per message

What makes it unique

vs alternatives

Avoids browser automation overhead (Selenium, Puppeteer) that adds latency and resource consumption; direct API access is faster and more reliable for agent-driven workflows than UI scraping

chunked-email-body-retrieval-with-streaming

Medium confidence

Solves for

Best for

LLM agents that need to understand full email content for decision-making

workflows processing emails with large attachments or complex MIME structures

systems with strict token budgets that require intelligent chunking

Requires

Gmail API credentials with message read scope

Valid access token with gmail.readonly or gmail.modify permission

Message ID from prior message list retrieval

Limitations

Chunking strategy not specified in repository — likely naive line-based or character-based splitting rather than semantic chunking

Attachment bodies are not fully retrieved — only metadata (filename, MIME type) is extracted

Large emails (>25MB) may hit Gmail API payload limits; no built-in streaming or resumable download

What makes it unique

Implements automatic chunking of email bodies to fit LLM context windows, handling MIME multipart structures natively rather than treating emails as opaque blobs

vs alternatives

More context-aware than naive email clients that load entire messages into memory; chunking prevents LLM token overflow without requiring manual email truncation by users

runtime-credential-injection-with-oauth-token-management

Medium confidence

Solves for

Best for

teams deploying MCP servers in containerized/Kubernetes environments

multi-tenant SaaS platforms that need per-user Gmail access

CI/CD pipelines and serverless functions that inject secrets at runtime

Requires

Valid Gmail OAuth 2.0 refresh token (obtained via prior authorization)

Google Cloud Project with OAuth 2.0 credentials (client ID, client secret)

Environment variables or MCP parameter injection mechanism

Limitations

Refresh token must be obtained out-of-band via OAuth 2.0 consent flow — MCP server does not implement the full OAuth flow

No built-in credential rotation or expiration monitoring — relies on Gmail API to reject expired tokens

Credentials stored in memory only — no persistence across server restarts; requires re-injection on each startup

What makes it unique

Eliminates local credential setup by accepting OAuth tokens at runtime, with automatic refresh logic that keeps workflows uninterrupted across token expiration boundaries

vs alternatives

email-composition-and-sending-with-mime-construction

Medium confidence

Solves for

Best for

LLM agents that need to take action by sending emails

automation workflows triggered by email events

systems that generate email responses dynamically based on AI reasoning

Requires

Gmail API credentials with gmail.send or gmail.modify scope

Valid access token with send permission

Recipient email address(es)

Limitations

Attachment support not explicitly documented — likely limited to small files (<25MB per Gmail API limits)

No built-in email template engine — requires pre-formatting of HTML bodies

No scheduling support — emails are sent immediately; no draft creation or delayed send

What makes it unique

Constructs MIME messages natively without external SMTP libraries, enabling email sending directly through Gmail API with automatic multipart handling for text/HTML alternatives and attachments

vs alternatives

mcp-protocol-integration-for-llm-agent-orchestration

Medium confidence

Solves for

Best for

teams building multi-tool AI agents with Claude or other LLMs

frameworks implementing MCP client support (e.g., Claude Desktop, custom agent runtimes)

organizations standardizing on MCP for tool integration across multiple services

Requires

MCP client implementation (Claude Desktop, custom agent framework, or MCP SDK)

Node.js runtime (likely — language not specified in repo)

MCP server configuration file or environment setup

Limitations

MCP protocol overhead adds latency (~50-100ms per tool call) compared to direct API calls

Tool schemas must be manually defined and kept in sync with implementation — no automatic schema generation

Error handling depends on MCP client implementation — some clients may not properly propagate Gmail API errors

What makes it unique

Exposes Gmail operations as MCP tools, enabling standardized integration with any LLM or agent framework that supports MCP, rather than requiring custom SDK bindings for each model

vs alternatives

MCP abstraction allows the same Gmail server to work with Claude, GPT-4, open-source LLMs, and custom agents without code changes; more flexible than model-specific plugins or SDKs

automatic-token-refresh-with-expiration-handling

Medium confidence

Solves for

Best for

long-running agents that process emails over extended periods

unattended automation workflows that cannot prompt for re-authentication

systems that need high availability and minimal manual intervention

Requires

Valid Gmail OAuth 2.0 refresh token

Google Cloud Project OAuth 2.0 credentials (client ID, client secret)

Network connectivity to Google's OAuth 2.0 token endpoint

Limitations

Refresh token itself does not expire in Gmail's standard implementation, but may be revoked by user — no handling for revocation detection

Token refresh adds latency (~500ms-1s) when triggered; no proactive refresh before expiration to avoid this latency

No metrics or logging for token refresh events — difficult to debug token-related issues in production

What makes it unique

Implements automatic token refresh with retry logic, allowing agents to operate continuously without manual re-authentication or explicit token management code

vs alternatives

More resilient than manual token refresh or static access tokens; prevents workflow interruptions due to token expiration, unlike basic Gmail client libraries that require explicit re-authentication

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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mcp-headless-gmail

Capabilities6 decomposed

headless-gmail-message-retrieval-with-pagination

chunked-email-body-retrieval-with-streaming

runtime-credential-injection-with-oauth-token-management

email-composition-and-sending-with-mime-construction

mcp-protocol-integration-for-llm-agent-orchestration

automatic-token-refresh-with-expiration-handling

Related Artifactssharing capabilities

@gongrzhe/server-gmail-autoauth-mcp

@gongrzhe/server-gmail-autoauth-mcp

@cardor/email-management

Gmail MCP Server

Gmail Email Management Server

MailSandbox

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Repository Details

About

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mcp-headless-gmail

Capabilities6 decomposed

headless-gmail-message-retrieval-with-pagination

chunked-email-body-retrieval-with-streaming

runtime-credential-injection-with-oauth-token-management

email-composition-and-sending-with-mime-construction

mcp-protocol-integration-for-llm-agent-orchestration

automatic-token-refresh-with-expiration-handling

Related Artifactssharing capabilities

@gongrzhe/server-gmail-autoauth-mcp

@gongrzhe/server-gmail-autoauth-mcp

@cardor/email-management

Gmail MCP Server

Gmail Email Management Server

MailSandbox

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Repository Details

About

Categories

Alternatives to mcp-headless-gmail

Are you the builder of mcp-headless-gmail?

Get the weekly brief

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