MCP for SLA monitoring gives an AI agent direct access to measured uptime, mean time to resolve (MTTR), mean time to acknowledge (MTTA), outages, and reliability risks. With Hyperping, you can ask Claude, Cursor, Codex, or another MCP client for an SLA report and get an answer based on your live monitoring data instead of copying numbers between dashboards.

The distinction between monitoring data and SLA compliance matters. Hyperping measures availability and incident response. Your agent can compare those results with a contractual target, but it also needs the SLA's measurement window, maintenance exclusions, and rounding rules before it can make a compliance judgment.

Quick answer

  • Hyperping exposes purpose-built reporting tools for uptime, MTTR, MTTA, monitor status, anomalies, and outages.
  • Synthetic checks measure the customer-facing endpoint from external regions, rather than relying only on metrics from inside your infrastructure.
  • Multi-region verification helps screen out local network failures before a failed check becomes an outage alert.
  • Project-scoped, read-only keys are the safest default for AI SLA reporting because they cannot change monitor configuration.
  • Your SLA terms still control the final calculation, including the target, reporting period, maintenance exclusions, and covered services.

How MCP for SLA monitoring works

The Model Context Protocol server in Hyperping exposes monitoring data as tools an AI client can call. The endpoint is https://api.hyperping.io/v1/mcp. It uses Streamable HTTP, Bearer token authentication, and one-project-per-key access.

When you ask, "What was production uptime last month?", the client selects get_monitor_uptime, supplies the date range and relevant monitor UUIDs, then formats the returned data. A more involved report can call several tools and combine the results in one answer.

MCP is the query layer in this workflow. Hyperping's uptime monitoring performs the checks and stores the history. The AI client chooses tools, applies your reporting instructions, and presents the result.

This separation is useful for two reasons. You do not have to give an agent database access, and you do not have to maintain a separate script for every report format. The project key limits what data the agent can reach. A read_only key also blocks every write operation.

Why external, multi-region checks matter for SLA data

An internal health metric can say that a service is running while customers cannot reach it through DNS, TLS, a CDN, or a public load balancer. Synthetic monitoring tests the endpoint from outside your infrastructure, closer to the path a customer takes.

Hyperping runs standard paid monitoring at 30-second intervals from locations worldwide. If a check fails, it verifies the failure across selected regions before alerting. That reduces the chance that a local routing problem is recorded as a service-wide incident.

The data source must still match the SLA. If your agreement measures one API endpoint in two named regions, query those monitors. If scheduled maintenance is excluded, provide the approved maintenance windows when asking the agent to judge attainment. An uptime percentage without this context is a monitoring result, not a complete contractual determination.

The most useful MCP tools for SLA reporting

Tool What it returns Useful SLA question
get_monitor_uptime(from?, to?, resolution?, monitor_uuids?) Aggregate and per-monitor uptime, with hourly, daily, weekly, or monthly resolution Did each covered service meet its availability target?
get_monitor_mttr(...) Mean time to resolve per monitor Which services take longest to recover?
get_monitor_mtta(...) Mean time to acknowledge per monitor How quickly does the team take ownership of incidents?
get_status_summary() Current monitor counts and down monitors with duration Is an active outage affecting the reporting snapshot?
get_monitor_anomalies(uuid) Flapping and latency-spike signals for one monitor Which service shows early reliability risk?
list_monitors(status?, page?, limit?) Monitors filtered by up, down, paused, or ssl_expiring Are paused checks or expiring certificates creating a coverage gap?

Pull uptime for a fixed SLA window

Use explicit start and end dates. "Last month" is convenient in conversation, but fixed dates make a report repeatable and easier to audit.

For example:

For monitor UUIDs A, B, and C, show uptime from 2026-06-01T00:00:00Z through 2026-06-30T23:59:59Z. Use daily resolution, rank monitors from lowest to highest uptime, and compare each result with a 99.9% target. Do not treat the result as compliant until I provide the SLA exclusions.

The monitor_uuids parameter keeps unrelated development or internal monitors out of the calculation. Daily resolution also makes it easier to find when a service consumed most of its downtime allowance.

Compare MTTR and MTTA

Uptime tells you whether customers could use the service. MTTR and MTTA show how your response process behaved after an incident started.

MTTA measures the time until someone acknowledged the incident. MTTR measures the time until it was resolved. Query both over the same date range and monitor set so comparisons remain meaningful.

A high MTTA points to alert routing, escalation, or ownership problems. A normal MTTA paired with high MTTR suggests the team responded promptly but recovery took too long. You can then inspect outage timelines or connect the result with on-call scheduling and escalation data.

Find the worst performers

Ask the agent to sort per-monitor uptime in ascending order rather than relying only on the project aggregate. One weak checkout or authentication endpoint can disappear inside a broad average.

For a useful weekly review, combine:

  1. get_monitor_uptime for availability and ranking.
  2. get_monitor_mttr and get_monitor_mtta for response performance.
  3. get_status_summary to flag anything still down.
  4. get_monitor_anomalies for each critical monitor that shows unusual behavior.

This produces a prioritized review list, not just a single percentage.

Check risks before they become downtime

get_monitor_anomalies(uuid) identifies flapping and latency spikes on a specific monitor. These signals do not change the SLA calculation by themselves, but they can show degradation before it becomes recorded downtime.

Certificate expiry belongs in the same preventive review. list_monitors(status: 'ssl_expiring') returns monitors whose certificates expire within 30 days. Ask the agent to separate certificates by urgency, then assign an owner before renewal becomes an availability incident.

Prompts for repeatable SLA workflows

These prompts are specific enough to produce comparable reports:

  • "Show uptime for all production monitor UUIDs from July 1 through July 31 UTC. Rank them from worst to best and flag anything below 99.95%."
  • "Compare MTTR and MTTA for the payments, authentication, and checkout monitors this quarter versus the previous quarter. Keep the date ranges equal."
  • "List the five monitors with the lowest uptime this month. For each one, include outage count, total downtime, MTTR, and whether it is currently down."
  • "Find paused production monitors and SSL certificates expiring within 30 days. Explain which SLA coverage gaps need an owner."
  • "Review anomalies for our critical API monitors. Separate latency spikes and flapping from events that created confirmed downtime."
  • "Create a customer-ready monthly reliability summary. State the monitoring window, included monitors, measured uptime, target, and any exclusions I still need to provide."

You can also connect Hyperping alongside CI/CD or incident-management MCP servers. The agent can compare an outage timeline with deploy timestamps, changes, acknowledgements, and ownership records. Treat correlation as a lead for investigation unless the available evidence establishes causation.

How to set up Hyperping for SLA monitoring

The reporting setup takes four steps. The full MCP documentation includes client configuration and the complete tool reference.

1. Create a read-only project key

Open Project Settings, select API Keys, and create a read_only key for the project that contains the covered monitors. Use separate keys when separate projects or reporting boundaries need to remain isolated.

2. Connect your MCP client

Add https://api.hyperping.io/v1/mcp as a Streamable HTTP server in Claude, Cursor, Codex, Windsurf, or another compatible client. Send the project key as an Authorization: Bearer header.

3. Run a baseline SLA query

Choose a fixed date range and an explicit list of monitor UUIDs. Ask for uptime, MTTR, and MTTA, then compare the output with the target and exclusions in your agreement.

4. Save a repeatable reporting prompt

Keep the same monitor scope, time zone, resolution, ranking, and output fields for each report. If your client or automation system can run scheduled prompts, use the saved prompt for a weekly engineering review or monthly customer report.

When to use a read_write key

SLA reporting rarely needs write access. Keep the reporting connection read-only unless the same workflow must create, update, pause, or resume monitors.

For example, an agent with a read_write key can pause a staging monitor during planned work or correct a monitor threshold. Hyperping does not expose a delete tool through MCP, so destructive removal stays outside this interface. Any production change should still require a clear approval step and a record of what changed.

Build the report around the agreement

The best MCP SLA workflow starts with a precise reporting contract: covered monitors, UTC boundaries, target percentage, approved exclusions, and required response metrics. Once those inputs stay consistent, the agent can query the same Hyperping tools and produce comparable reports without another custom script.

Start with a read_only project key and one monthly report. You can create a Hyperping account, follow the MCP setup guide, or read six broader ways to use the Hyperping MCP server for incident triage, on-call lookup, and monitor management.