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export_subscribers

Export all subscribers matching your filters, with full engagement metrics and no paging. Waits for Substack to generate the file and returns parsed records.

Instructions

Export subscribers with their full column values, including the engagement metrics list_subscribers can filter on but not return: email opens over 7d/30d/6mo, unique emails seen, post views, unique posts seen, comments, shares, links clicked, days active and activity rating. Takes the same filters as list_subscribers and covers the whole matching set — there is no paging. Substack generates the file asynchronously, so this waits for it and returns the parsed records. One column cannot be exported and is reported in missing_columns rather than failing: tag_ids.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoFree-text search over subscriber name and email.
columnsNoWhich columns to include. Defaults to every column. Available: user_name = Name; user_email_address = Email; country = Country; state = State/Province; group_membership = Group membership; subscription_type = Type; subscription_created_at = Start date; subscription_expires_at = Expiration date; first_payment_at = First paid date; last_subscribed_at = Paid upgrade date; unsubscribed_at = Cancel date; subscription_interval = Subscription interval; stripe_plan_name = Stripe plan; free_attribution = Subscription source (free); paid_attribution = Subscription source (paid); is_subscribed = Can see paid content; bestseller_tier = Bestseller; total_revenue_generated = Revenue; num_subs_gifted = Subscriptions gifted; bundle_id = Bundle; is_bundle_parent = Bundle origin; num_emails_received = Emails received (6mo); num_emails_dropped = Emails dropped (6mo); num_email_opens = Emails opened (6mo); num_email_opens_last_7d = Emails opened (7d); num_email_opens_last_30d = Emails opened (30d); num_unique_email_posts_seen = Unique emails seen (6mo); num_unique_email_posts_seen_last_7d = Unique emails seen (7d); num_unique_email_posts_seen_last_30d = Unique emails seen (30d); last_opened_at = Last email open; links_clicked = Links clicked; last_clicked_at = Last clicked at; emails_enabled = Sections; num_web_post_views = Post views; num_web_post_views_last_7d = Post views (7d); num_web_post_views_last_30d = Post views (30d); num_unique_web_posts_seen = Unique posts seen; num_unique_web_posts_seen_last_7d = Unique posts seen (7d); num_unique_web_posts_seen_last_30d = Unique posts seen (30d); num_comments = Comments; num_comments_last_7d = Comments (7d); num_comments_last_30d = Comments (30d); num_shares = Shares; num_shares_last_7d = Shares (7d); num_shares_last_30d = Shares (30d); days_active_last_30d = Days active (30d); activity_rating = Activity; tag_ids = Tags
filtersNoWhich subscribers to export, using the same conditions as list_subscribers, combined with AND. Omit to export everyone.
max_wait_secondsNoHow long to wait for Substack to generate the file, 1-600, defaulting to 120. A small export is ready in a few seconds.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.3.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so well: it discloses asynchronous file generation, waiting behavior, return of parsed records, absence of paging, and the special handling of tag_ids via missing_columns instead of failure. These are exactly the traits an agent needs beyond the schema.

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 dense but every sentence earns its place: purpose, differentiation, behavioral mechanics, and an edge case. The most important information is front-loaded, and there is no redundant filler.

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

Completeness4/5

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

The tool has a rich schema and clear parameter descriptions, and the description covers the key non-obvious behaviors: async wait, no paging, same filters, and missing_columns. Since there is no output schema, a bit more detail about the exact parsed record shape would be ideal, but the description is otherwise sufficient for correct invocation.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful parameter context by explaining that filters mirror list_subscribers, that columns include engagement metrics, that tag_ids appears in missing_columns, and that max_wait_seconds relates to the async generation wait.

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

Purpose5/5

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

The description states a specific verb and resource — exporting subscribers with full column values — and explicitly contrasts with list_subscribers by noting the engagement metrics list_subscribers can filter on but cannot return. The 'no paging' and 'whole matching set' details further distinguish it from sibling tools.

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

Usage Guidelines5/5

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

The description directly references list_subscribers as the alternative, clarifying that the same filters are reused and that export_subscribers returns the engagement metrics list_subscribers cannot. It also warns there is no paging, which signals the appropriate context for using this tool versus list_subscribers.

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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