@imqueue
Search docs, scaffold code
- Category
- Developer Tools
- Primary Subcategory
- Developer Docs & Reference Search
Integration details
Description
@imqueue is an open-source TypeScript framework for building microservices that talk over a message queue instead of HTTP — you write a class, decorate the methods you want to publish, and callers get a fully-typed client generated from the running service. This server gives your assistant first-hand knowledge of it, so it writes real @imqueue code instead of plausible-looking code. search_docs covers the guides, the tutorial, the CLI manual, the articles, and every exported symbol of every @imqueue package that publishes an API reference — so you can ask a question in plain words ("how do I expose a service method?") or look up an exact signature ("RedisQueue.send", "IMQOptions.safeDelivery"). Results carry page URLs, and get_doc returns any page as plain markdown for reading and quoting. list_packages returns the current package catalogue with install commands, which is how an assistant picks the right one rather than guessing at a name. Where two packages cover the same ground — tracing, or the database layer — the results carry the rule for choosing exactly one, because installing both breaks quietly rather than loudly. scaffold_service generates an idiomatic service — an IMQService subclass with @expose()d, JSDoc-typed methods plus a bootstrap that starts it — from the method signatures you describe. A custom return type comes back with the @classType() and @property() decorators it needs, which matters because a field that lacks them reaches the generated client typed any and still compiles. scaffold_client shows how to generate and use the typed client for a service. Both return source text for you to review and paste; neither writes a file. All six tools are read-only. The server has no accounts, no authentication and no storage: each request is handled statelessly, and the only data it sees is the argument you send — a search query, a doc URL, a service name. Nothing is retained, and no conversation content is collected or used for training. Tools that would act on your own machine — driving the imq CLI, creating projects on disk, starting and stopping your services, reading their logs — are deliberately not part of this server, because a hosted server cannot reach your machine and should not claim to. They ship in the local install instead (npx -y @imqueue/mcp), and local_install_guide returns the setup steps for it.
- Integration type
- Plugin
- Verification status
- Not applicable
- Platform
- ChatGPT
- Primary Subcategory
- Developer Docs & Reference Search
- Secondary Subcategories
- None listed
- Brand
- @imqueue
- Access
- No account required
- First tracked
- 2026-08-21
- Tool count
- 7
- Geography
- US
The Primary Subcategory used for this profile’s headline score.
Other Subcategories where the Integration is listed.
ChatGPT Plugin Discovery Score
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What discovery looks like

Competing in ChatGPT Developer Docs & Reference Search
View Category7 tools agents can invoke
How do I improve a ChatGPT Plugin's discoverability?
The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.
What are @imqueue alternatives on ChatGPT?
As of 2026-09-12, @imqueue competes with Arez, Autodesk Product Help, Context7, Ezoic Setup, EzzyBills, GitBook, Metaplay SDK Docs, Relewise Developer, RideDesk, Soracom Knowledge, SourcePRD in ChatGPT Developer Docs & Reference Search, ranked by public Discoverability Score.
Where is this profile measured?
This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.