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IT management ChatGPT plugins were a group of third party extensions for ChatGPT focused on tasks that information technology teams handle every day, including server administration, infrastructure provisioning, network monitoring, cloud architecture, and workflow automation. They were part of the broader ChatGPT plugins program operated by OpenAI between March 2023 and April 2024. The IT management category sat next to other technical groups such as software development ChatGPT plugins and programming ChatGPT plugins inside the ChatGPT plugin store, and overlapped with all of them on practical use cases like running scripts, querying logs, and generating infrastructure code.
The category never had a stable, official membership list. OpenAI did not publish a formal taxonomy for the plugin store, and third party catalogs grouped plugins differently. The whole framework was retired in 2024 in favor of custom GPTs and the GPT Store.
OpenAI announced the ChatGPT plugins program on March 23, 2023, calling it a way to let ChatGPT "access up to date information, run computations, or use third party services." [1] The launch shipped with twelve partner plugins (Expedia, FiscalNote, Instacart, KAYAK, Klarna, Milo, OpenTable, Shopify, Slack, Speak, Wolfram, and Zapier) and two first party tools, Browsing and Code Interpreter. None of the original twelve were aimed strictly at IT operations, although the Slack plugin and the Zapier plugin were quickly adopted for routine ticket and notification work.
Access opened up gradually. ChatGPT Plus subscribers received broad rollout on May 12, 2023, and the plugin store grew from a handful of partner integrations to several hundred third party tools by the middle of 2023. By the time the store was frozen, researchers counted more than one thousand published plugins. [2]
The program ended in two stages in 2024. On March 19, 2024, OpenAI disabled new plugin installations and prevented users from starting new conversations with plugins enabled. On April 9, 2024, all existing plugin conversations were shut down, ending live access to every plugin in the store. [3] OpenAI directed users toward custom GPTs, which had launched on November 6, 2023 at the DevDay event, and toward the GPT Store, which opened to ChatGPT Plus subscribers on January 10, 2024. The Actions feature inside custom GPTs replaced the plugin manifest model with a similar, but more flexible, OpenAPI based design.
IT management is a broad term in industry, covering ticket handling, monitoring, asset tracking, identity, deployment pipelines, and the day to day operation of servers and networks. The plugin store reflected that breadth without naming a single "IT management" tab. Plugin directories that tried to organize the store after the fact placed IT focused plugins in groupings such as Infrastructure, Monitoring, Workflow Automation, and Database. [4]
For the purposes of this article, IT management plugins are the ones used for at least one of the following recurring jobs:
Plugins that focused on writing or analyzing application source code are described in the companion articles on software development ChatGPT plugins and programming ChatGPT plugins. There was real overlap, since infrastructure as code blurred the line between deployment work and pure development.
The following table lists IT management oriented plugins that were verifiably available in the ChatGPT plugin store at some point between mid 2023 and the April 2024 shutdown. Descriptions reflect the wording the developers used in the plugin store at the time. [5][6][7]
| Plugin | Developer or sponsor | Function |
|---|---|---|
| AutoInfra1 | AutoInfra | Connected ChatGPT to servers on AWS, Google Cloud, Microsoft Azure, or any host reachable over SSH, exposing a Linux command line for administration, log analysis, and metric review. |
| ChatSSHPlug | Independent developer | Translated natural language requests into SSH commands run against a configured server, with output returned inside the ChatGPT conversation. |
| Power Automate | Microsoft | Let users discover, create, and run Power Automate flows from ChatGPT, drawing on more than one thousand connectors that Microsoft offered for enterprise systems. |
| Cloud Diagram Gen | Independent developer | Generated cloud architecture diagrams for patterns such as three tier, microservices, serverless, multi cloud, big data, and content delivery, marketed as an unofficial AWS plugin. |
| Cloudflare Radar | Cloudflare | Surfaced internet traffic, attack, and outage data from Cloudflare's global network, useful for capacity planning and incident triage. |
| A Monitoring Expert (Network Monitor) | Mahadeva Co. | Walked users through setting up host checks for HTTP, HTTPS, ICMP, DNS, SMTP, and raw socket targets, including a quantum safe encryption check. |
| ne.tools | ne.tools | Ran lightweight network diagnostics such as DNS lookups, WHOIS queries, and IP reputation checks. |
| Surveillance API | Independent developer | Exposed Synology Surveillance Station API documentation and code generation for video surveillance integrations. |
| Website Performance | Independent developer | Reported performance, accessibility, search engine optimization, and progressive web application metrics for a given URL. |
| HackTrack | Independent developer | Checked whether credentials linked to an email address had appeared in known data breaches. |
| Quantum Ready Check | Independent developer | Tested whether a website used quantum safe key exchange, an emerging concern for long lived secrets. |
| AskYourDatabase | Independent developer | Connected to relational databases over a connection string and translated questions into SQL, used for schema review and operational reporting. |
| AgentSQL | Independent developer | Allowed conversational queries against Snowflake warehouses and CSV files. |
| SingleStore | SingleStore | Let users query SingleStore databases in plain English, useful for operational dashboards. |
| Zapier | Zapier | Bridged ChatGPT to thousands of business and IT applications, widely used to file tickets, send Slack messages, and update spreadsheets from a chat session. The Zapier plugin was retired alongside the rest of the program in April 2024. [8] |
The IT category also included a long tail of small utilities for traceroute style lookups, certificate inspection, and basic uptime checks. Many of these plugins were operated by single developers, and most have not preserved their original manifests on the public internet now that the store is closed.
Every ChatGPT plugin shared the same machinery. The plugin developer published an OpenAPI specification describing the endpoints the plugin offered and a small JSON manifest at a .well-known/ai-plugin.json URL. The manifest gave the plugin's name, a short description for users, a longer description for the model, authentication metadata, and a pointer to the OpenAPI document. ChatGPT used the manifest plus the OpenAPI definitions to assemble TypeScript style pseudocode that became part of the system prompt at runtime. [3] When the model decided to call a plugin, it produced a function call against one of the documented endpoints, ChatGPT executed the HTTPS request on the user's behalf, and the JSON response was injected back into the conversation.
For IT management work this design had several practical consequences:
| Aspect | Effect on IT plugins |
|---|---|
| Authentication | Most server, cloud, or database plugins required users to register an account with the plugin developer or paste an API token, raising clear questions about credential custody. |
| Action limits | Each plugin could only do what its OpenAPI definition described, so a plugin like ChatSSHPlug could exec shell commands but could not, for example, modify firewall rules unless an additional endpoint was published. |
| Single shot calls | Plugins ran one HTTPS request at a time, which made multi step playbooks (collect logs, correlate, file a ticket) feel stitched together. |
| Manifest visibility | Manifests were public by design, so descriptions and example prompts were essentially product marketing read by the model. |
The model behind the conversation was usually GPT-4 for ChatGPT Plus subscribers, who were the only users with access to the plugin store. Plugin authors often relied on careful prompt engineering inside the manifest description to steer the model toward correct use of their endpoints, since the large language model had no other context about the system being managed.
IT teams used these plugins more for ad hoc inspection than for day to day production operations. Common patterns included:
| Pattern | Plugins typically used |
|---|---|
| Read only diagnostics on a server (disk space, top processes, recent log lines) | AutoInfra1, ChatSSHPlug |
| Quick draft of a cloud reference diagram for a design review | Cloud Diagram Gen |
| External health check of a domain or certificate | A Monitoring Expert, ne.tools, Website Performance, Quantum Ready Check |
| Triage of a suspected breach involving leaked credentials | HackTrack |
| Pulling internet weather and attack trends into an incident bridge | Cloudflare Radar |
| Translating a human request into a Power Automate or Zapier workflow | Power Automate, Zapier |
| Asking shaped questions of an operational database without writing SQL by hand | AskYourDatabase, AgentSQL, SingleStore |
The attraction was speed. Pulling a one off DNS lookup or generating a quick architecture diagram inside a chat session was faster than opening a separate dashboard. The trade off was reproducibility. Plugin output lived inside a conversation and was not, by default, captured by an audit system the way a runbook execution would be.
IT teams that piloted these plugins ran into a consistent list of problems.
| Concern | Practical impact |
|---|---|
| Credential handling | A plugin that could SSH into production servers or query a database needed durable secrets. The plugin store did not enforce a uniform secrets model, so teams either trusted the developer or scoped the plugin to a sandbox account. |
| Auditability | Plugin actions were logged inside ChatGPT but not, by default, sent to the customer's own audit system. Compliance regimes that required immutable command logs found this awkward. |
| Reliability | Plugins were operated by their developers on independent infrastructure. When a plugin's host went down, it disappeared from ChatGPT until the developer restored it. |
| Drift between manifest and reality | If the underlying tool changed and the manifest did not, ChatGPT could call deprecated endpoints with confident, but wrong, language. |
| Permission scopes | Most plugins were all or nothing, with no native concept of role based access control inside the plugin contract. |
| Security research findings | A 2024 academic survey of the store found a meaningful fraction of plugins exposed manifest files inappropriately or had broken access control. [2] |
For those reasons, most production IT teams used these plugins for read only inspection or for sandbox experiments. Heavier work, such as actually deploying changes from a chat session, stayed inside change managed pipelines.
The IT management category sat between several adjacent groups in the ChatGPT plugin categories framework.
| Adjacent category | Overlap with IT management |
|---|---|
| Software development ChatGPT plugins | Code search, repository inspection, and CI helpers were often used by the same engineers running infrastructure plugins. |
| Programming ChatGPT plugins | Plugins that ran or compiled code were used by IT teams for quick scripting alongside infrastructure tools. |
| Workflow automation | Zapier and Power Automate spanned office productivity and IT use cases. |
| Database and analytics | AskYourDatabase, AgentSQL, and SingleStore appeared in both IT and analytics directories, depending on whether the database in question stored operational telemetry or business metrics. |
| Monitoring and infrastructure | The networking, uptime, and traffic plugins formed a small but distinct sub group. |
This overlap is one reason there was no canonical IT management list. A user who wanted to triage a slow web application might pull from four or five different categories in a single session.
Once custom GPTs landed in November 2023, OpenAI made it clear that the plugin store was on a glide path to retirement. Custom GPTs allowed authors to combine instructions, knowledge files, and Actions in one package, and Actions used essentially the same OpenAPI based contract as plugins. Many IT plugin authors rebuilt their tools as custom GPTs published through the GPT Store after January 10, 2024.
From the IT operator's point of view the changeover meant a few practical shifts:
| Before (plugins) | After (custom GPTs and Actions) |
|---|---|
| User enabled up to three plugins per chat | A custom GPT bundles its Actions, instructions, and knowledge once for the whole conversation. |
| Plugin manifests were the only place to set behavior, with limited room for written guidance | Custom GPTs accept long natural language instructions plus uploaded files. |
| Discovery happened inside the plugin store, ranked roughly by popularity | Discovery moved to the GPT Store, with categorized browsing and creator profiles. |
| Authentication was per plugin, with limited revocation | Actions inherit OpenAI's per user OAuth flow, which gives finer grained control. |
Because the underlying contract is similar, most workable IT plugins from 2023 had close successors as custom GPTs. The names changed in some cases, and a number of single developer plugins were not rebuilt at all, but the category as a class of work outlived the plugin store. The IT management plugins of 2023 and early 2024 were the first widely available example of a large language model calling production tools through a standardized contract, and many lessons about authentication, reliability, and audit logging that show up in later agent platforms were first surfaced inside that ecosystem.
See also: ChatGPT Plugins, ChatGPT Plugin Categories and IT Management