Provider REST API
ObservabilityConnect Claude to Datadog
Search logs, query metrics, and triage monitors, incidents, and hosts. Toolspoke puts 14 of its actions behind one MCP endpoint that Claude, Cursor, and Codex all speak.
- Connection
- Provider REST API
- Authentication
- API and application keys
- Actions exposed
- 14
- Cost per call (typical)
- 1 credit
- Adapter
- Maintained by Toolspoke
Connected in three steps
- 1
Install Datadog
Open the marketplace in your workspace, add Datadog to the project your agents work in, and it appears on the gateway immediately.
- 2
Connect the credential
Authenticate with api and application keys. Where to get one, and what it has to be able to reach, is the next section.
- 3
Point your agent at the gateway
Give your client one address, https://toolspoke.com/mcp. Claude Code takes it as a command, Claude and Claude Desktop add it as a custom connector, and Cursor, Codex and VS Code each read it from a config file of their own.
.mcp.json{
"mcpServers": {
"toolspoke": {
"type": "http",
"url": "https://toolspoke.com/mcp"
}
}
}One block covers every tool you have installed. Datadog shows up in the client as soon as your policy allows it, and so does everything else you install later.
Where the address goes, per client
- Claude Code
Run it in your project, then /mcp to sign in
claude mcp add --transport http toolspoke https://toolspoke.com/mcp- Claude and Claude Desktop
Settings, then Connectors, then Add custom connector
https://toolspoke.com/mcp- Cursor
~/.cursor/mcp.json, or .cursor/mcp.json for one project
{ "mcpServers": { "toolspoke": { "url": "https://toolspoke.com/mcp" } } }- Codex
~/.codex/config.toml
[mcp_servers.toolspoke] url = "https://toolspoke.com/mcp"- VS Code
.vscode/mcp.json, or the MCP: Add Server command
{ "servers": { "toolspoke": { "type": "http", "url": "https://toolspoke.com/mcp" } } }
What Datadog asks for
API and application keys. You provide it once, when you install the connector. Toolspoke encrypts it at rest and decrypts it only for the length of a single call, and the gateway attaches it to the outbound request itself, so it is never part of the arguments an agent sends.
- API keyRequired
- Datadog → Organization Settings → API Keys. Sent as the DD-API-KEY header.
- …
- Application keyRequired
- Datadog → Organization Settings → Application Keys. Sent as DD-APPLICATION-KEY. Reads inherit the scopes of the key, so give it at least monitors_read, dashboards_read, incident_read and logs_read_data.
- …
- Site API URLOptional
- The API host for your Datadog site: https://api.datadoghq.com (US1), https://api.datadoghq.eu (EU1), https://api.us3.datadoghq.com, https://api.us5.datadoghq.com, https://api.ap1.datadoghq.com. Keys are not valid across sites.
- https://api.datadoghq.com
What Claude can do in Datadog
14 actions, each one declared and named by the connector rather than discovered at runtime. A workspace policy grants a person all of them, a hand-picked selection, everything on the read side, everything on the write side, or none.
- Reads
- 12Reads
- Writes
- 1Writes
- Destructive
- 1Destructive
Reads
12Fetches data and changes nothing.
search_logsReturn individual log events matching a Datadog log search query, newest first. Use this when you need the actual lines around an incident; use aggregate_logs when you want counts, rates or a breakdown instead, because a raw search of a noisy service will fill a context window without answering the question. Time bounds accept Datadog's relative syntax (now-15m, now-1h) as well as ISO 8601.
aggregate_logsCount or measure logs instead of listing them, optionally broken down by a facet. This is the right first call for "how many errors, by service, in the last hour" - it returns a handful of buckets rather than thousands of lines. Follow up with search_logs on the worst bucket to read the actual events.
query_timeseriesEvaluate a Datadog metric query over a time window and return the points. The query uses Datadog's own syntax, e.g. "avg:system.cpu.user{env:prod} by {host}" or "sum:trace.http.request.errors{service:checkout}.as_rate()". Call list_metrics first if you do not know the exact metric name. Timestamps are epoch milliseconds.
list_metricsList the metric names that have reported since a point in time, so query_timeseries can be given a name that actually exists. `from` is epoch SECONDS, not milliseconds, and is required by Datadog - pass the start of the period you care about.
list_monitorsList monitors with their current alert state, which is the fastest way to see what is alerting right now. Returns the numeric monitor ids that get_monitor, mute_monitor and unmute_monitor need. Filter with name for a substring of the monitor title, or tags for the scope a monitor watches.
get_monitorFetch one monitor by its numeric id: its query, thresholds, notification message, current state and per-group states. Call list_monitors first to find the id. Use this before muting anything, so the mute is applied to the monitor you meant.
list_eventsSearch the Datadog event stream - deploys, monitor transitions, integration events and anything posted through the events intake. Use it to line an alert up against a deployment. Reverse it with a query like "source:github" or "tags:service:checkout". Time bounds accept Datadog's relative syntax.
list_incidentsList Datadog incidents newest first, with their state, severity and commander. Use it to see what is currently declared before deciding whether an alert is already being handled, then pass an id to get_incident. Requires the Incident Management product and an application key with incident_read.
get_incidentFetch one incident by its UUID: title, state, severity, timeline fields, and the users attached to it. Call list_incidents first for the id. Pass include to pull related records back in the same call rather than making a second one.
list_dashboardsList dashboards with their ids, titles and authors. Use it to find the dashboard id that get_dashboard needs; the widget definitions are not included here.
get_dashboardFetch one dashboard by id, including its widget definitions and the metric queries behind them. This is the quickest way to learn which queries a team already trusts for a service - read the widgets, then re-run one through query_timeseries. Deeply nested widget groups are trimmed.
list_hostsList hosts reporting to Datadog with their tags, apps and mute status. Hosts seen in the last three hours are returned by default; pass `from` as epoch seconds to widen that. Use it to confirm whether a host stopped reporting at all, which no metric query can tell you.
Writes
1Creates or updates something on the other side.
unmute_monitorRestore notifications for a monitor that mute_monitor silenced. Pass the same scope that was muted to lift one scope; omit it to clear the monitor's mute entirely.
Destructive
1Deletes or permanently alters something. Worth granting on purpose.
mute_monitorSilence a monitor so it stops notifying, optionally only for one scope and only until a given time. This changes what the on-call rota sees: while a monitor is muted nobody is paged for it, so always set `end` unless a human has asked for an open-ended mute. Reverse it with unmute_monitor.
What it will not do
Enforced by the gateway rather than left to convention, which is why each of these can be stated flatly.
- It cannot call anything else
- The 14 actions above are the whole of it. A call to any other name is refused before it reaches Datadog rather than forwarded on, and connecting your account does not add to the list: it is fixed by the connector, not discovered at run time.
- It reaches no further than your credential
- Toolspoke holds no access to Datadog of its own. Every call carries the credential you stored and nothing besides, so whatever that credential cannot reach, this connector cannot reach either.
- It never hears from Datadog
- Nothing is pushed to it. There is no webhook, no subscription and no polling, so this connector cannot notice by itself that something changed in Datadog. An agent has to ask.
- It does not smooth over provider limits
- Toolspoke does not retry, queue or back off around Datadog's own rate limits. A call that Datadog refuses comes back to the agent as a failed call.
Before you connect it
What can Claude do in Datadog?
14 named actions: 12 that only read, 1 that write and 1 that delete or permanently alter something. They include search_logs, aggregate_logs and query_timeseries. Nothing outside that list is reachable: the connector declares each operation by name rather than proxying whatever an agent asks for.
What credentials does the Datadog connector need?
API and application keys. The connector asks for api key and application key, and optionally site api url. Values are encrypted at rest and attached to the outbound request by the gateway, so they are never part of the arguments an agent sends and never reach the audit log.
Does the Datadog connector work with Cursor and Codex, or only Claude?
Any client that speaks MCP, and every one of them gets the same 14 actions. There is a single address, https://toolspoke.com/mcp. Claude Code adds it with claude mcp add --transport http, Claude and Claude Desktop take it as a custom connector in settings, Cursor reads it from .cursor/mcp.json, Codex from ~/.codex/config.toml, and VS Code from .vscode/mcp.json. Each of them signs in to the gateway itself, so there is no key to paste.
What does the Datadog connector not do?
The 14 actions above are the whole of it. A call to any other name is refused before it reaches Datadog rather than forwarded on, and connecting your account does not add to the list: it is fixed by the connector, not discovered at run time. Toolspoke holds no access to Datadog of its own. Every call carries the credential you stored and nothing besides, so whatever that credential cannot reach, this connector cannot reach either. Nothing is pushed to it. There is no webhook, no subscription and no polling, so this connector cannot notice by itself that something changed in Datadog. An agent has to ask. Toolspoke does not retry, queue or back off around Datadog's own rate limits. A call that Datadog refuses comes back to the agent as a failed call.
Can I limit which actions an agent can call?
Yes, in two places. The project switches Datadog's actions on and off one at a time, for everyone in the project at once, and the screen groups them by read, write and destructive so turning off everything that deletes is one click. An individual agent key can then be narrowed further, to particular toolkits in a project and to particular actions in a toolkit. Whatever it was granted, a key never reaches a project its owner cannot.
What gets recorded when an agent calls Datadog?
Every attempt, with the agent that made it and the person that agent belongs to, the full request payload, the response payload, the status, the duration, and the credits spent. Values whose key names a secret are masked out before the record is shown to anyone. An operation the connector marks as not retained never has its response body written at all, so the gateway keeps no second copy of what was read.