Apple Mail MCP Server
Allows read-only interaction with Apple Mail on macOS, enabling listing mailboxes, searching emails by keyword and date, and reading email content.
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., "@Apple Mail MCP ServerList all my email mailboxes"
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.
Apple Mail MCP Server (READ ONLY)
A minimal, read-only MCP (Model Context Protocol) server that lets Claude Desktop interact with Apple Mail on macOS. Uses AppleScript via subprocess — no third-party email libraries, no network calls.
Version
Current: 1.3.0
Versioning follows Semantic Versioning:
MAJOR — breaking changes to the tool API or behaviour
MINOR — new tools or non-breaking feature additions
PATCH — bug fixes and security hardening
Related MCP server: macos-mail-mcp
What it can do
Tool | Description |
| List every account and mailbox configured in Apple Mail |
| Search emails by keyword and/or date; scans subject+sender via AppleScript |
| Read the full content of a specific email by its opaque ID |
What it will never do
Delete, trash, move, or archive any email
Send, reply, forward, or compose any message
Write any file to disk or export data
Make network requests or external connections
Access or decode email attachments
Provide analytics or aggregate statistics (beyond optional per-mailbox message counts, which exist only to help choose search scope)
Prerequisites
macOS (Apple Mail is macOS-only)
Python 3.10 or later
Apple Mail configured with at least one account
Claude Desktop (or any MCP-compatible client)
Setup
Quick install (uv)
If you have uv installed, you can skip cloning and the virtual environment entirely — add this to ~/Library/Application Support/Claude/claude_desktop_config.json under "mcpServers":
{
"mcpServers": {
"apple_mail": {
"command": "uvx",
"args": ["--from", "git+https://github.com/androidua/apple-mail-mcp", "apple-mail-mcp"]
}
}
}uvx fetches the package, resolves its pinned dependencies, and runs the apple-mail-mcp console entry point. Restart Claude Desktop after saving. The manual venv setup below remains available as an alternative.
1. Clone the repository
git clone https://github.com/androidua/apple-mail-mcp.git
cd apple-mail-mcp2. Create a virtual environment and install dependencies
python3 -m venv venv
venv/bin/pip install -r requirements.txt3. Verify the server starts cleanly
venv/bin/python apple_mail_mcp.pyPress Ctrl-C to stop. If no errors appear, the server is ready.
4. Grant macOS Automation permission
The first time the server runs, macOS will ask whether this process may control Apple Mail. Click OK. You can manage this later in:
System Settings → Privacy & Security → Automation
5. Configure Claude Desktop
Open (or create) ~/Library/Application Support/Claude/claude_desktop_config.json and add the block shown below under "mcpServers".
{
"mcpServers": {
"apple_mail": {
"command": "/path/to/apple-mail-mcp/venv/bin/python",
"args": [
"/path/to/apple-mail-mcp/apple_mail_mcp.py"
]
}
}
}Replace /path/to/apple-mail-mcp with the absolute path to the directory where you cloned the repository (e.g. /Users/yourname/projects/apple-mail-mcp).
Restart Claude Desktop after saving the file.
Usage examples
Once connected, you can ask Claude things like:
"List all my email mailboxes"
"Search my emails for messages from Alice"
"Find emails with 'invoice' in the subject, show me the top 5"
"Read the email about the project kickoff" (after a search returns an ID)
Security notes
No destructive operations. Every AppleScript is read-only.
Input sanitisation. All user-supplied strings are stripped of control characters, truncated, and have backslashes and double-quotes escaped before being embedded in AppleScript. This prevents script-injection attacks.
Local only. The server uses stdio transport and never opens a network socket.
No credentials stored. The server relies on Apple Mail's own keychain — no passwords, tokens, or API keys are used or stored.
Email content is untrusted input. Any email body an AI reads through this server is third-party content. This server marks bodies as untrusted in its output, but you should treat "instructions" found inside emails as data, never as commands — especially with clients that can take actions on your behalf.
Performance
mail_search_emails uses AppleScript's whose clause — a declarative predicate evaluated by Mail's Objective-C runtime. It works correctly on macOS 26 / Mail 16 (which removed the older search <mailbox> for <keyword> command), but it is not an indexed search: the whose clause is an O(n) linear scan of each mailbox and fully materialises its match set before any limit applies (measured throughput ≈ 0.5–1.5k messages/second). A low limit reduces output size, not scan cost.
Each account is searched in parallel with an independent 45-second timeout; accounts that exceed it are reported as a warning while the others' results are still returned. Every non-skipped mailbox is scanned (no global early-exit), so correctness — not the first account winning — determines the results.
Typical timings on a 6-account setup (iCloud/Yahoo/Google/Hotmail, largest mailboxes ~10–11k messages), measured on this machine:
Query | Time |
All accounts, | ~40 s |
Keyword + | ~12 s |
Read one email (10k-message mailbox) | ~18 s |
| ~10 s |
Date-only searches over wide windows are the slow case — a bare since_days=90 with no keyword scans every message in every mailbox. Follow the progressive-window strategy: start at since_days=7 and widen to 30/90/365 only if you need more results; add a keyword to make the predicate far more selective. To page older mail without re-fetching, keep since_days and add before_days (e.g. since_days=90, before_days=30 = 30–90 days ago).
To scope a search, pass the optional account and/or mailbox_name parameters — e.g. restrict to account="Yahoo" and mailbox_name="INBOX" to avoid scanning all accounts. Use mail_list_mailboxes(include_counts=true) to see which mailboxes are large before choosing a scope.
Body-content search is intentionally unsupported in the AppleScript engine — whose content contains forces a full body download for every message, which is impractically slow on real mailboxes.
Troubleshooting
Symptom | Fix |
| Go to System Settings → Privacy & Security → Automation and enable Mail for your Python process. |
| Open Apple Mail and ensure at least one account is signed in. |
Tool times out | Use |
| Always pass the |
Project structure
apple-mail-mcp/
├── apple_mail_mcp.py # MCP server — single file, all tools
├── requirements.txt # Pinned dependencies
├── README.md # This file
└── venv/ # Local virtual environment (not committed)Changelog
1.3.0 — 2026-07-17
Fix (accuracy, critical): cross-account searches are now merged, deduplicated and sorted newest-first — previously the first responding account filled the whole result list and other accounts' matches were silently dropped (e.g. an all-accounts
since_days=7returned 10/10 results from one account, hiding five others with no warning)Fix (accuracy): Gmail duplicate-view mailboxes (All Mail, [Gmail]All Mail, Important, Starred) and real-world junk/trash names (Bulk, Junk Email, Deleted Items, Outbox) are now skipped by default; new
include_all_mailboxes=trueopts back inFix:
mail_read_emailtimeout raised to 60 s (reads on 10k+ mailboxes ran up against the old 30 s limit); recipients without display names no longer render as "missing value"Feature:
before_daysbounds the search window's near edge for paging older mail without re-fetchingFeature:
mail_list_mailboxesacceptsinclude_counts=truefor per-mailbox message counts (search-scoping metadata)Feature: MIT license, pyproject packaging (
uvxone-line install), pytest suite, GitHub Actions CI, server-level MCP instructions, correct advertised server versionDocs: honest performance documentation (the
whoseclause is an unindexed O(n) scan, ~0.5–1.5k msgs/sec); prompt-injection warning for email content
1.2.1 — 2026-03-25
Fix (critical): remove
proc.stdout.close()/proc.stderr.close()—asyncio.StreamReaderhas no.close()method; calling it on timeout causedAttributeErrorthat crashed the tool and surfaced as the "StreamReader object has no attribute 'close'" error users saw for slow IMAP accountsFix: redesign multi-account search to run per-account in parallel using
asyncio.gather(return_exceptions=True)— a slow or offline account (Yahoo!, Hotmail, etc.) can no longer block or crash results from other accounts; each account gets an independent 45-second timeoutFix: when a specific
accountis provided the original single-script path is preserved (60 s timeout); parallel path is used only for cross-account searchesUX: results now include a warning listing which accounts timed out, rather than crashing silently
1.2.0 — 2026-03-25
Feature:
mail_search_emailsnow acceptssince_days(integer, 1–365) to filter emails by date received — supports natural queries like "last 7 days", "yesterday", "past month"Feature:
keywordis now optional inmail_search_emails— browse recent mail without a search term (e.g.since_days=1returns today's mail)Both filters are combinable:
keyword="invoice" + since_days=30returns invoice emails from the past monthResult headers and "no results" messages now reflect which filters were active
Note: body content search is intentionally not supported — AppleScript's
whose content containsforces a full body download for every message, making it impractically slow on real mailboxes
1.1.4 — 2026-03-25
Fix (regression): revert
_script_read_emailto proven account/mailbox iteration — direct AppleScript addressing (mailbox X of account Y) was unreliable for non-standard account types (Gmail, Exchange, shared accounts)Fix (regression): revert
mail_search_emailsJSON output to flat array[...]— the{"results": [...]}wrapper introduced in v1.1.3 broke Claude AI's ability to extractemail_idvalues from resultsFix: improve AppleScript error categorisation — errors now return actionable messages (Mail not running, Automation permission denied, item not found) instead of a generic fallback; raw AppleScript error text is still logged internally
1.1.3 — 2026-03-25
Fix (reliability): close asyncio pipe transports before
await proc.wait()on timeout — prevents file descriptor accumulation under repeated Mail.app timeoutsFix (reliability): anchor
---BODY_START---split to a leading newline — prevents a subject line containing that exact string from corrupting header parsing inmail_read_emailFix (security): parse search output fields from both ends of the delimiter-split record — a
\x1fbyte in a subject no longer shifts sender/date/is_read columnsFix (security): extend
_CTRL_STRIP_REto cover C1 controls U+0080–U+009F (including U+0085 NEL which Python'ssplitlines()treats as a line terminator)Fix (security): log raw
osascriptstderr internally; return a generic error string to callers instead of forwarding script fragmentsPerf: replace nested account/mailbox iteration in
_script_read_emailwith direct AppleScript object addressing (mailbox X of account Y) — O(1) lookup instead of O(accounts × mailboxes) name scanDocs: correct
whosedocstring — it is O(n) per mailbox, not indexed; lowlimitdoes not reduce scan costUX: search results now report a warning when rows were silently skipped due to parse errors
1.1.2 — 2026-03-09
Fix: replaced backslash line-continuation characters (
\) in the_script_read_emailAppleScript template with sequential assignments — AppleScript uses¬for continuation, not\; the invalid characters caused allmail_read_emailcalls to fail with AppleScript syntax error -2741
1.1.1 — 2026-03-09
Fix: replaced
search <mailbox> for <keyword>AppleScript command with awhoseclause filter — thesearchcommand was removed in Mail 16 (macOS 26) and caused allmail_search_emailscalls to fail with an AppleScript syntax error
1.1.0 — 2026-03-09
Performance:
mail_search_emailsnow uses Apple Mail's native indexed search (search <mailbox> for <keyword>) instead of brute-force message iteration — dramatically faster on large mailboxes (e.g. Yahoo with 20+ years of email)Feature: added optional
accountandmailbox_nameparameters tomail_search_emailsfor scoped searches (e.g. search only Yahoo / INBOX)Default exclusion: Trash, Deleted Messages, Junk, Spam, Bulk Mail are skipped automatically unless explicitly targeted via
mailbox_name
1.0.0 — 2026-03-09
Initial release
Tools:
mail_list_mailboxes,mail_search_emails,mail_read_emailRead-only, AppleScript-based, no network calls
Input sanitisation against AppleScript injection
Available Tools
3 toolsmail_list_mailboxesARead-onlyIdempotent
List all mailboxes/folders available in Apple Mail, grouped by account.
Queries Apple Mail via AppleScript to retrieve every configured account and all mailboxes within each account (INBOX, Sent Messages, Drafts, custom folders, etc.). Strictly read-only — no emails are modified and no network calls are made.
Args: params (ListMailboxesInput): Input containing: - response_format (str): 'markdown' (default) or 'json'. - include_counts (bool): Add per-mailbox message counts to help choose search scope. Slower on many-mailbox setups. Default false.
Returns: str: Formatted list of all accounts and their mailboxes.
Markdown example:
# Apple Mail Mailboxes
## iCloud
- INBOX
- Sent Messages
- Drafts
JSON example:
[
{"account": "iCloud", "mailbox": "INBOX"},
{"account": "iCloud", "mailbox": "Sent Messages"}
]Examples: - Use when: "What mailboxes do I have?" → default params - Use when: "List my email folders as JSON" → response_format="json"
Error Handling: Returns an error string if Mail.app cannot be reached or there are no configured accounts. Prompts the user to open Mail.app if needed.
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, but the description strongly reinforces 'Strictly read-only — no emails are modified and no network calls are made.' It also details error handling (Mail.app unreachable, no accounts), exceeding the annotations' context.
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 well-organized with summary, parameters, return format, examples, and error handling. It could be slightly shorter but every section adds unique value; no redundant 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?
Given the simple listing nature, annotations, and output schema, the description completely covers purpose, behavior, parameters, return format with both Markdown and JSON examples, and error handling. Additional context (AppleScript, performance hints) makes it fully actionable.
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?
Despite 0% schema coverage, the description provides full parameter details: 'include_counts' includes performance trade-off advice ('10k-message mailbox scans in ~10-20s'), and 'response_format' explains default vs. JSON. This adds significant meaning beyond the schema's own 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 that the tool lists all mailboxes/folders in Apple Mail, grouped by account. It uses specific verbs ('list') and resource ('mailboxes/folders'), and the distinction from sibling tools is clear since siblings handle reading and searching specific emails.
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?
Examples show when to use the tool ('What mailboxes do I have?') and when to switch format. However, no explicit when-not-to-use or direct comparison to alternatives is given, though it's implied by the distinct purposes of siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mail_read_emailARead-onlyIdempotent
Read the full content of a specific Apple Mail email by its ID.
Decodes the opaque email_id produced by mail_search_emails, locates the message in Apple Mail, and returns its complete content: subject, sender, recipients (To, CC), date received, read-status, and full body text.
Strictly read-only — the message read-status is NOT changed by this call.
Args: params (ReadEmailInput): Input containing: - email_id (str): Opaque ID from mail_search_emails. Required. - response_format (str): 'markdown' (default) or 'json'.
Returns: str: Full email content.
Markdown example:
# Email: Invoice for March
- **From**: billing@example.com
- **To**: you@icloud.com
- **CC**: (none)
- **Date**: Monday, 3 March 2025 at 09:14:02
- **Read**: Yes
- **Mailbox**: iCloud / INBOX
## Body
Hi there, please find your invoice attached...
JSON example:
{
"subject": "Invoice for March",
"sender": "billing@example.com",
"to": "you@icloud.com",
"cc": "",
"date": "Monday, 3 March 2025 at 09:14:02",
"read": true,
"account": "iCloud",
"mailbox": "INBOX",
"body": "Hi there, please find your invoice attached..."
}Examples: - Use when: "Read the email about invoices" (after searching) → pass the email_id from search results - Don't use when: You don't have an email_id yet → use mail_search_emails first
Error Handling: - Returns an error if the email_id is malformed or expired. - Returns an error if the message cannot be found (e.g. deleted since search). - Returns an error if Mail.app cannot be reached. - Reads on very large mailboxes (>30k messages) can take up to a minute; the mailbox is rescanned per read.
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds that the message read-status is NOT changed, provides performance caveats for large mailboxes, and explains error conditions, all beyond what annotations provide.
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 well-structured with clear sections (purpose, args, returns, examples, error handling, notes). It is thorough yet concise, with no unnecessary content.
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 read tool with detailed input schema and annotations, the description is complete: it covers purpose, parameters, return format with examples, error handling, and performance notes. No gaps are apparent.
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 already has detailed descriptions for both parameters, so schema coverage is high. The description reiterates these but adds value through examples of return formats and usage context, justifying a score above baseline.
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 it reads the full content of a specific Apple Mail email by its ID, using the verb 'Read' and specifying the resource. It distinguishes from sibling tools by noting that mail_search_emails provides the ID needed for this tool.
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 explicit usage guidance: use after searching with mail_search_emails, and not without an email_id. It includes examples and a clear 'Don't use when' section, which helps the agent decide correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mail_search_emailsARead-onlyIdempotent
Search Apple Mail for emails by keyword and/or date range.
Searches across all configured accounts in parallel, then merges, deduplicates and sorts the results newest-first. System/junk/duplicate-view mailboxes are excluded by default (see include_all_mailboxes). Returns matching emails with opaque email_id values for use with mail_read_email.
IMPORTANT — date range strategy (always follow this order): Large date windows (since_days > 90) are slow on big IMAP accounts and frequently timeout. Always start narrow and expand only if needed:
Step 1: since_days=7 → if results < needed, continue
Step 2: since_days=30 → if results < needed, continue
Step 3: since_days=90 → if results < needed, continue
Step 4: since_days=365 → last resort only
Never jump straight to since_days=365 for vague queries like
"recent emails" or "last few emails". Start with 7 days.
To page further back, keep since_days and add before_days instead of
re-reading overlapping results.Args: params (SearchEmailsInput): Input containing: - keyword (str): Optional search term matched against subject and sender. Omit when filtering by date only. - since_days (int): Optional. Restrict to emails received in the last N days (1–365). Use 1=today, 7=week, 30=month. - limit (int): Max results to return (default 20, max 100). - account (str): Optional. Restrict to one account (e.g. 'iCloud'). - mailbox_name (str): Optional. Restrict to one mailbox (e.g. 'INBOX'). - before_days (int): Optional. Exclude emails newer than N days ago; combine with since_days to page an older window (e.g. since_days=90, before_days=30 → 30–90 days ago) without re-fetching newer results. - include_all_mailboxes (bool): Optional. Also search normally-skipped mailboxes (Trash, Junk/Spam/Bulk, Deleted Items, Gmail All Mail/ Important/Starred, Outbox). Default false. - response_format (str): 'markdown' (default) or 'json'.
At least one of keyword or since_days must be provided.Returns: str: Results are merged across accounts, deduplicated by message id (Gmail label copies collapse to one), and sorted newest-first. System/junk/duplicate-view mailboxes (Trash, Deleted Items, Junk/Spam/Bulk, Gmail All Mail/Important/Starred, Outbox) are skipped unless include_all_mailboxes=true. Each result carries subject, sender, date, read-status and an opaque email_id. Timed-out accounts are listed as a warning (not a crash).
Markdown example:
# Search Results: "invoice" · last 30 days
Found 3 email(s) ...
JSON example:
[{"email_id": "...", "account": "iCloud", "mailbox": "INBOX",
"subject": "Invoice", "sender": "x@y.com",
"date": "Mon 3 Mar 2025", "read": true}]Examples: - "Most recent 3 emails" → since_days=7, limit=3 (expand to 30/90 if < 3 found) - "Emails this week" → since_days=7 - "Invoices in the past month" → keyword="invoice", since_days=30 - "Find emails from Alice" → keyword="Alice", since_days=30 - "Search only Yahoo INBOX" → account="Yahoo", mailbox_name="INBOX", since_days=7
Error Handling: - Returns an error string if Mail.app cannot be reached. - Returns "No emails found" with filter description if no matches. - Accounts that exceed the 45 s per-account timeout are listed as warnings; other accounts' results are still returned.
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses parallel search, deduplication, sorting, exclusion of system mailboxes, and error behavior (timeouts, no results). Annotations already mark it as read-only and idempotent; description adds context 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?
The description is well-structured with sections for args, returns, examples, and error handling. It is somewhat lengthy but efficiently organized and front-loaded with the critical date strategy.
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?
Covers purpose, all parameters, usage strategy, error handling, and return format comprehensively. Given an output schema exists and the description is thorough, it provides complete guidance for correct tool invocation.
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 detailed descriptions for each parameter (high coverage), but the description adds extra value with usage examples and strategic advice (e.g., start with since_days=7). Baseline 3 is exceeded due to this added context.
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 'Search Apple Mail for emails' with specific verbs and resources. It distinguishes from sibling tools like mail_read_email (which reads a single email) and mail_list_mailboxes (which lists mailboxes).
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?
Provides extensive usage guidance including a step-by-step date range strategy, examples mapping common queries to parameters, and instructions for paging. However, it does not explicitly compare to mail_read_email or mail_list_mailboxes, though it implies usage of email_id for reading.
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.
3 tool updates
v1.3.0- First observed
mail_list_mailboxes - First observed
mail_read_email - First observed
mail_search_emails
TDQS
Each tool has a clearly distinct purpose: mail_list_mailboxes lists folders, mail_search_emails finds emails, and mail_read_email retrieves full content. No overlap in functionality.
All tools follow the consistent pattern mail_verb_noun (mail_read_email, mail_list_mailboxes, mail_search_emails), using snake_case throughout.
Three tools is an appropriate size for a focused email reading/searching server. Each tool is necessary and there is no bloat.
The tool surface is severely limited to read-only operations. There is no ability to send, delete, mark as read/unread, move, or manage emails, which are core email tasks an agent would typically need.
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