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How to Build a Remote Search Function for Slack Enterprise Search

A practical guide to connecting an external content source to Slack Enterprise Search with a custom function, valid results, optional filters, and synchronous event handling.
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Slack’s Enterprise Search lets an app connect an external content source to Slack search through a custom function. This guide uses that interpretation of “All Remote”: the title does not identify a platform, and Slack’s developer documentation describes this specific remote-search implementation. The function must return structured results within Slack’s execution window; it is not the same as calling Slack’s API to search messages and files.

Choose the right kind of Slack search

Use an Enterprise Search function when you want people to search an external system from Slack’s search experience. Your app receives a query and returns results from that external source in Slack’s required format.

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Slack’s search.all method serves a different purpose: it searches Slack messages and files programmatically. It requires the search:read scope for a user token, and its response groups matches by content type. It does not implement a custom search connector for an external source.

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Configure the app manifest and event subscription

Slack’s Enterprise Search developer guide describes the app configuration and function contract. Add a search object inside the manifest’s features block, and set search_function_callback_id to the callback ID of the custom function that returns results. If you implement filters, you can also set search_filters_function_callback_id to the callback ID of the function that provides them.

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Subscribe the app to the function_executed event. Define the custom step function that returns search results and make its callback ID match the one in the manifest. If your app also implements entity details, Slack’s example includes the entity_details_requested event; include that event only for that capability.

Implement the search function’s inputs

The search function requires the user’s query. Filters are optional. You can also add inputs typed as slack#/types/user_context to receive context about the user running the search.

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Do not assume the query is the exact text the user typed. Slack may parse and rewrite it before passing it to your function for consistency, security, and the search experience. Treat the received query as the input to your connector, rather than relying on a verbatim copy of the original wording.

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Return results in Slack’s required shape

Return a search_results output containing no more than 50 result objects. Every result needs these fields:

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  • external_ref, an object with a required id that uniquely identifies the result; its type is optional.
  • title, the result’s title.
  • description, a description of the result.
  • link, a link to the item in its source system.
  • date_updated, a date in YYYY-MM-DD format, not a timestamp.

The optional content field can provide more detailed text for AI answers. The description is cropped in the results interface, so distinguish the short text a person sees in the result list from detail that may be available to the AI-answer path. Keep titles and descriptions useful on their own, and use a stable external ID so the same source item can be recognized consistently.

Finish the event synchronously and within 10 seconds

Slack’s developer documentation says apps must handle function_executed events synchronously so search results arrive quickly. Complete the function and supply its output before acknowledging the event. Slack documents functions.completeSuccess for successful execution and functions.completeError for failures; the execution must finish within 10 seconds. When returning an error, provide a user-facing message through completeError.

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This limit makes the external search request part of the function’s critical path. Design the connector to return promptly, cap its response at 50 results, and handle source-system failures by completing with an error instead of leaving the event unacknowledged.

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Add filters only when the source can support them

A filter function is optional. It returns a filter array with up to five filter objects. Each object requires a machine-readable name, human-readable display_name, and type. Slack documents multi_select and toggle filter types. A multi-select filter also needs options, each with a display name and a unique value.

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Successful filter results are cached per user for up to three minutes and are not requested again until the search context changes. Keep filter definitions aligned with the values your external source can actually query; a filter shown in Slack is only useful if the connector applies it meaningfully.

Account for caching and distribution limits

Slack caches successful search results for each user and query for up to three minutes. Associated AI answers are cached for the same period. A successful result may therefore not reflect an immediate source-system change during that window.

Slack states that apps using Enterprise Search cannot be distributed publicly or submitted to the Slack Marketplace. Account for that restriction when deciding how to deploy the connector and who needs access.

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Implementation checklist

  1. Add features.search.search_function_callback_id to the manifest and match it to the custom result function’s callback ID.
  2. Subscribe to function_executed; add the optional filter callback configuration and function only if filters are part of the experience.
  3. Accept the required query and any optional filter or user-context inputs without assuming the query is untouched raw text.
  4. Return at most 50 results with a unique external reference ID, title, description, link, and YYYY-MM-DD update date.
  5. Complete each event with functions.completeSuccess or functions.completeError before acknowledging it, and keep execution within 10 seconds.
  6. Plan for per-user caching and the restriction on public distribution and Marketplace submission.

How this differs from federated search in Elastic

Elastic Workplace Search documents a separate remote-source model in which the source’s search endpoint is queried at request time. Its 8.19 documentation says remote or all-source searches disable features such as filters, boosts, facets, and automatic query refinement because remote endpoints may not support them, and gives a 10,000-millisecond default remote timeout. That page is marked no longer updated, so treat it as a description of that documented version, not current implementation guidance for new Elastic deployments. It is not a substitute for Slack’s Enterprise Search app contract.

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