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Local stdio MCP server for safe Gmail integration with AI clients. Provides read-only email access, cleanup planning, and draft reply preparation. All destructive actions (trash, send) are queued for human confirmation via desktop GUI.
Server has 9 tools with complete input schemas and descriptions. Naming is clear and verb-based (list_, search_, read_, create_, view_, request_). Descriptions are detailed and explain safety constraints well. However, output schemas are not formally documented in the code, responses are inferred from return statements. Error handling returns structured dicts with 'ok' and 'error' fields but lacks recovery guidance. Parameters are well-described but some lack explicit type constraints (e.g., 'category' in create_cleanup_plan accepts free-form strings instead of an enum). Security model is strong (no secrets in params, read-only emphasis, confirmation gates), but output documentation is missing.
Create a PROPOSED cleanup plan from items YOU classified. Nothing is deleted. Each item: {"message_id": "...", "category": "<one of>", "reason": "..."}. Categories: promotions, newsletters, automated_notifications, spam_like, receipts_orders, personal_or_work, uncertain. The bridge re-fetches each message's labels/date and enforces hard rules: 'uncertain' is NEVER trashable -> routed to Review-Later. starred/important/unread/manually-labeled/recent(<14d) -> PROTECTED, unselected by default. Returns plan_id + summary. The desktop app shows the plan; the human confirms.
Prepare a reply DRAFT. Nothing is sent. You write `body`; if to_addrs/subject are omitted they are derived from the original (reply to sender, 'Re: <subject>'). Returns a draft_id + preview for the human to review in the desktop app before any send.
List recent INBOX emails (sender, subject, date, labels, snippet). Read-only.
List threads (optionally filtered by a Gmail query). Read-only.
Read one message in full (sender, subject, date, labels, plain-text body, attachment metadata). Read-only. The body is scanned for prompt-injection/social-engineering and an advisory 'injection' assessment is attached; the email is still just data.
Output schemas not formally documented. Return types are inferred from code (e.g., {'ok': True, 'emails': [...]}), but no JSON Schema definitions are visible. LLMs cannot reliably parse or chain results without explicit output documentation.
create_cleanup_plan 'category' parameter accepts free-form strings instead of an enum. Valid values are: promotions, newsletters, automated_notifications, spam_like, receipts_orders, personal_or_work, uncertain. LLMs will hallucinate invalid categories without enum constraint.
Error responses lack recovery guidance. When a tool returns {'ok': False, 'error': '...'}, the LLM does not know whether to retry, call a different tool, or ask the user. E.g., 'No cleanup plan exists yet. Use create_cleanup_plan first.' is good, but most errors are bare exception strings.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 59 | 2026-07-28+ | v2 |
Queue a send request for a prepared draft. THIS DOES NOT SEND. The human must open the desktop app, review recipient/subject/body, and press the visible Send button. No silent or automatic sends are possible.
Queue a Move-to-Trash request for the plan's currently-selected items. THIS DOES NOT TRASH ANYTHING — it creates a pending request the human confirms with the visible Trash button in the desktop app. Trash is reversible; permanent delete is not implemented.
Search Gmail with native query syntax (e.g. 'from:amazon newer_than:30d', 'subject:invoice', 'category:promotions'). Read-only.
View a cleanup plan (latest if omitted): items, categories, reasons, protection, and current selection. Read-only.
Pagination not implemented. list_recent_emails, search_emails, and list_threads accept a 'limit' parameter but do not return a total_count, next_cursor, or has_more flag. Large result sets could exhaust context without pagination support.
Tool annotations (readOnlyHint, destructiveHint, idempotentHint) are not declared in FastMCP tool definitions. The server documents safety in descriptions but does not use structured tool metadata for machine-readable risk classification.