Connect Datadog to OpenAI (ChatGPT)

Detect the Datadog region for the connected account. Call this FIRST before any other Datadog tool if you do not already know the region. Returns the region domain (e.g. datadoghq.com) which must be passed as the region parameter to **Search Logs**, **Search Monitors**, **Get Metric Data**, and all other Datadog tools. See the docs

Detect the Datadog region for the connected account by validating the API key against each regional endpoint. Use this to discover the correct region before calling other Datadog actions. See the docs

Query time-series metric data for analyzing trends and system performance. Query syntax: avg:system.cpu.user{*}, sum:requests.count{env:prod} by {host}, max:system.mem.used{service:web}. Both from and to are POSIX timestamps in seconds. Use **Search Metrics** first to discover available metric names. Use **Search Hosts** to find valid host tags for scoping. After finding anomalies, use **Search Logs** to investigate related entries. See the docs

Get a list of logs matching a filter query. Uses the GET endpoint with a higher rate limit (3600/hr vs 300/hr). See the docs

Post custom time-series metric data points to Datadog. Data appears in dashboards, monitors, and can be queried via **Get Metric Data**. Points: JSON object where keys are Unix timestamps (seconds) and values are numeric, e.g. {"1640995200": 1.0}. Use **Search Metrics** to verify a metric name exists, or post to a new name to create it. This is a WRITE operation that creates or appends data to a metric time series. See the docs

List and search Datadog dashboards. Returns dashboard IDs, titles, URLs, and metadata. Dashboard URL: https://app.{region}/dashboard/{id} where region comes from **Get Account Info**. Use alongside **Search Services** to find dashboards related to a specific service. See the docs

Search Datadog events: monitor state changes, deployment markers, error spikes, and infrastructure events. Filter by sources (e.g. nagios,docker), tags (e.g. env:prod,service:web), and priority (normal or low). Time range defaults to last 24h (POSIX timestamps in seconds). To investigate a monitor alert, use **Search Monitors** first, then search events for the relevant time range. Follow up with **Search Logs** for deeper investigation. See the docs

Search monitored infrastructure hosts. Filter by tag (env:production), name (host:web-01), or partial match. Sort by cpu, iowait, load, status, or apps. Host names from results can scope queries in **Get Metric Data** (e.g. avg:system.cpu.user{host:web-01}), filter logs in **Search Logs** (host:web-01), or filter metrics in **Search Metrics**. Max 1000 results. See the docs

Search Datadog incidents by state, severity, and metadata. Query syntax: state:active, state:resolved, severity:SEV-1. After finding an incident, investigate with: **Search Logs** for the incident time window, **Get Metric Data** for relevant metrics, **Search Events** for related monitor alerts, and **Search Services** for ownership info. See the docs

Search Datadog logs matching a query with support for facets and time ranges. Uses log search syntax: service:web-app status:error, @http.status_code:>=400, boolean operators (AND, OR, NOT), and wildcards. Set from to now-1h for recent logs. Use **Search Metrics** to discover metric names or **Search Hosts** to find host names for filtering. To investigate an incident, use **Search Incidents** first, then search logs for that time window and service. See the docs

Discovery tool: list available Datadog metric names, optionally filtered by host. Returns metric name strings (e.g. system.cpu.user, aws.ec2.cpuutilization) for use in **Get Metric Data** queries with the syntax aggregation:metric.name{tags}. Use **Search Hosts** to find valid host names for the host filter. See the docs

Search Datadog monitors (alerting rules) including status, thresholds, and conditions. Query syntax: tag:env:production, type:metric, status:Alert. Tags filter: comma-separated (e.g. env:prod,team:backend). After finding a monitor, use **Search Events** to see recent state changes, or **Get Metric Data** to query the underlying metric it tracks. Returns monitor ID, name, type, query, status, and tags. See the docs

List services from Datadog's Service Catalog with ownership, metadata, and team info. Use to discover service names for filtering in **Search Logs** (service:my-app) or finding monitors via **Search Monitors** (tag:service:my-app). Returns service definitions including links, docs, and on-call. See the docs

The Chat API, using the gpt-3.5-turbo or gpt-4 model. See the documentation

Chat using the web search tool. See the documentation

Chat with your models and allow them to invoke functions. Optionally, you can build and invoke workflows as functions. See the documentation

Chat with your files knowledge base (vector stores). See the documentation

Summarizes text using the Chat API. See the documentation

Classify items into specific categories using the Chat API. See the documentation

Translate text from one language to another using the Chat API. See the documentation

Transcribes audio into the input language. See the documentation

Creates an image given a prompt returning a URL to the image. See the documentation

Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. See the documentation

OpenAI recommends using the **Chat** action for the latest gpt-3.5-turbo API, since it's faster and 10x cheaper. This action creates a completion for the provided prompt and parameters using the older /completions API. See the documentation

Send a message or question about an image and receive a response. See the documentation

Cancels a run that is in progress. See the documentation

Sends a message and generates a response, storing the message history for a continuous conversation. See the documentation

Send a chat via the Responses API, mixing built-in tools and MCP server tools. See the documentation.

Generates audio from the input text. See the documentation

Creates an assistant with a model and instructions. See the documentation

Creates and executes a batch from an uploaded file of requests. See the documentation

Creates a job that fine-tunes a specified model from a given dataset. See the documentation

Classifies if text is potentially harmful. See the documentation

Creates a thread with optional messages and metadata, and optionally runs the thread using the specified assistant. See the documentation

Create a vector store. See the documentation

Create a vector store file. See the documentation

Deletes a specified file from OpenAI. See the documentation