Rank #1 of 5 in Incident Management & On-call
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See what an agent can do with incident.io before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; commands tagged live-capable can re-run against the real endpoint from our edge, right now (▶ run live — the exact same request, live and recorded lines always labeled); the live MCP handshake runs real requests from our edge, right now — including, where the server allows it, one real read-only tool call (bring your own key for auth-gated servers); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).
$curl -si -X POST https://mcp.incident.io/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'recorded session — replayed, not liveVerified integrations
Connections to other tracked products — hover a chip for the verbatim evidence quote behind it.
By theme — the product's score on each story themeBy theme
Agenticness — how well agents can access and operate the productAgenticnessevidence →
How well agents can access and operate the product
Ai incident — stories about ai incident in this arenaAi incidentevidence →
Stories about ai incident in this arena
Alerting escalation — stories about alerting escalation in this arenaAlerting escalationevidence →
Stories about alerting escalation in this arena
Analytics reliability — stories about analytics reliability in this arenaAnalytics reliabilityevidence →
Stories about analytics reliability in this arena
Automation depth — how much of the product can run unattendedAutomation depthevidence →
How much of the product can run unattended
Automation runbooks — stories about automation runbooks in this arenaAutomation runbooksevidence →
Stories about automation runbooks in this arena
Incident response — stories about incident response in this arenaIncident responseevidence →
Stories about incident response in this arena
Integrations observability — stories about integrations observability in this arenaIntegrations observabilityevidence →
Stories about integrations observability in this arena
Mobile experience — stories about mobile experience in this arenaMobile experienceevidence →
Stories about mobile experience in this arena
On call scheduling — stories about on call scheduling in this arenaOn call schedulingevidence →
Stories about on call scheduling in this arena
Openness — open source, data portability, and self-hosting storiesOpennessevidence →
Open source, data portability, and self-hosting stories
Postmortems learning — stories about postmortems learning in this arenaPostmortems learningevidence →
Stories about postmortems learning in this arena
Privacy posture — data-handling and privacy storiesPrivacy postureevidence →
Data-handling and privacy stories
Status communication — stories about status communication in this arenaStatus communicationevidence →
Stories about status communication in this arena
Story verdicts — every judged story with its evidenceStory verdicts
Follow the green: where the map greys out is where incident.io stops today. ✓ full · ~ partial · ! disputed · — none · n/a not applicable.
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
API surface
Drive the product through a documented public API
✓8/10
unlocks → Official CLI · First-party integrations cover my observability stack — Datadog, Grafana, Prometheus, CloudWatch, Sentry — with documented setup
Subscribe to events via webhooks
✓7/10
Build against official SDKs
~4/10
Issue scoped/least-privilege API credentials for an agent
~3/10
Connect an agent via an official MCP server
✓9/10
Download a machine-readable API spec (OpenAPI or equivalent)
✓9/10
Rely on versioned APIs with a documented deprecation policy
~3/10
Test against a sandbox environment without touching production data
~3/10
Explore an interactive API reference with runnable examples
~4/10
Docs for agents
Point an agent at llms.txt or agent-oriented docs
✓8/10
Agentic features
Delegate tasks to a built-in AI assistant inside the product
✓8/10
unlocks → MCP client
Operate the product with natural-language commands
✓8/10
Plug MCP servers into this product so it can use their tools
—0/10
Get AI-generated insights and suggestions from my data inside the product
✓8/10
Set up automations that run autonomously in the background
✓8/10
Ai incident — stories about ai incident in this arenaAi incident
Stories about ai incident in this arena
Alerting escalation — stories about alerting escalation in this arenaAlerting escalation
Stories about alerting escalation in this arena
Escalation policies walk unacknowledged pages through multiple steps — delays, fallback responders, and repeat rounds — until someone acknowledges
~6/10
Duplicate and related alerts are deduplicated and grouped so one incident pages one human, not fifty
✓8/10
Pages reach me over the channels I choose — push, SMS, phone call, and email — with per-channel notification rules
—0/10
Alerts from my monitoring tools are ingested through documented sources and routed to the right team by conditions I define
✓8/10
Analytics reliability — stories about analytics reliability in this arenaAnalytics reliability
Stories about analytics reliability in this arena
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
Automation depth
Define rules that trigger actions automatically on events
~5/10
unlocks → Versioned workflows · Runbooks attach to incidents and their steps can trigger automatically — creating channels, assigning tasks, running diagnostics
Schedule recurring jobs or workflows
—0/10
Perform bulk operations across many items at once
—0/10
Version, review, and roll back my automations
—0/10
Automation runbooks — stories about automation runbooks in this arenaAutomation runbooks
Stories about automation runbooks in this arena
Incident response — stories about incident response in this arenaIncident response
Stories about incident response in this arena
Internal stakeholders get structured incident updates they can subscribe to, without joining the war room
~5/10
Incidents carry defined roles (commander, comms lead) and task checklists so response stays coordinated under pressure
—–
Declare and run an incident from chat — Slack or Teams — with channels, roles, and updates created for me
✓7/10
The incident timeline is captured automatically — alerts, actions, and chat decisions — and I can edit or annotate it afterwards
✓8/10
Integrations observability — stories about integrations observability in this arenaIntegrations observability
Stories about integrations observability in this arena
Mobile experience — stories about mobile experience in this arenaMobile experience
Stories about mobile experience in this arena
On call scheduling — stories about on call scheduling in this arenaOn call scheduling
Stories about on call scheduling in this arena
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
Postmortems learning — stories about postmortems learning in this arenaPostmortems learning
Stories about postmortems learning in this arena
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
Status communication — stories about status communication in this arenaStatus communication
Stories about status communication in this arena
Sorted by importance (agentic first) (high → low) · 54/54 stories · click a row’s chevron for the rationale and evidence
Connect an agent via an official MCP server G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 9/10 | Tprobed⚿ | |
Delegate tasks to a built-in AI assistant inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 8/10 | Cclaimed | |
Drive the product through a documented public API G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 8/10 | Tprobed | |
Plug MCP servers into this product so it can use their tools G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | none | 0/10 | ⚿ | |
Download a machine-readable API spec (OpenAPI or equivalent) G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 9/10 | Tprobed | |
Get AI-generated insights and suggestions from my data inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Cclaimed | |
Operate the product with natural-language commands G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Tprobed⚿ | |
Point an agent at llms.txt or agent-oriented docs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Tprobed | |
Set up automations that run autonomously in the background G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Cclaimed | |
Run the product headlessly / in CI for automation G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 7/10 | Tprobed | |
Subscribe to events via webhooks G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 7/10 | Cclaimed | |
Build against official SDKs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 4/10 | Tprobed | |
Explore an interactive API reference with runnable examples G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 4/10 | Tprobed | |
Issue scoped/least-privilege API credentials for an agent G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 3/10 | Tprobed⚿ | |
Rely on versioned APIs with a documented deprecation policy G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 3/10 | Tprobed | |
Use an official CLI G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Test against a sandbox environment without touching production data G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 1 | partial | 3/10 | Tprobed | |
Alerts from my monitoring tools are ingested through documented sources and routed to the right team by conditions I define C Routing | sre | Alerting escalation — stories about alerting escalation in this arenaAlerting escalation | 3 | full | 8/10 | Cclaimed | |
AI writes the incident as it happens — live summaries, drafted updates, and scribed call notes — so responders respond instead of typing C Ai summaries | ai-native user | Ai incident — stories about ai incident in this arenaAi incident | 3 | full | 7/10 | Cclaimed | |
Declare and run an incident from chat — Slack or Teams — with channels, roles, and updates created for me C Declaration | on-call engineer | Incident response — stories about incident response in this arenaIncident response | 3 | full | 7/10 | Cclaimed | |
My agent can acknowledge, escalate, and resolve incidents end to end through a documented API or MCP connection — no dashboard in the loop C Agent ops | ai-native user | Ai incident — stories about ai incident in this arenaAi incident | 3 | partial | 7/10 | Tprobed⚿ | |
Postmortems follow a real workflow — templates, drafting from the timeline, review, and publication G Postmortems | engineering leader | Postmortems learning — stories about postmortems learning in this arenaPostmortems learning | 3 | partial | 7/10 | Cclaimed | |
Build on-call schedules with rotations, layers, time zones, and round-robin coverage that match how my teams actually work C Schedules | sre | On call scheduling — stories about on call scheduling in this arenaOn call scheduling | 3 | partial | 6/10 | Cclaimed | |
Escalation policies walk unacknowledged pages through multiple steps — delays, fallback responders, and repeat rounds — until someone acknowledges C Escalation | sre | Alerting escalation — stories about alerting escalation in this arenaAlerting escalation | 3 | partial | 6/10 | Cclaimed | |
Define rules that trigger actions automatically on events G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 3 | partial | 5/10 | Cclaimed | |
Export all of my data in open formats and leave G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | partial | 4/10 | Tprobed | |
First-party integrations cover my observability stack — Datadog, Grafana, Prometheus, CloudWatch, Sentry — with documented setup C Alert sources | sre | Integrations observability — stories about integrations observability in this arenaIntegrations observability | 3 | none | 0/10 | ||
Prevent my data from being used to train AI models G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 3 | none | untested | none yet | |
Self-host the core product G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | n/a | untested | none yet | |
AI drafts the postmortem from the incident record — timeline, contributing factors, follow-ups — ready for human review G Ai summaries | ai-native user | Ai incident — stories about ai incident in this arenaAi incident | 2 | full | 8/10 | Cclaimed | |
An AI investigator digs into the probable cause — correlating changes, telemetry, and similar past incidents — before a human even asks C Ai investigation | ai-native user | Ai incident — stories about ai incident in this arenaAi incident | 2 | full | 8/10 | Cclaimed | |
Duplicate and related alerts are deduplicated and grouped so one incident pages one human, not fifty C Noise reduction | sre | Alerting escalation — stories about alerting escalation in this arenaAlerting escalation | 2 | full | 8/10 | Cclaimed | |
The incident timeline is captured automatically — alerts, actions, and chat decisions — and I can edit or annotate it afterwards C Timeline | sre | Incident response — stories about incident response in this arenaIncident response | 2 | full | 8/10 | Cclaimed | |
Publish a hosted public status page — custom domain, subscriber notifications — driven from incident state G Status pages | engineering leader | Status communication — stories about status communication in this arenaStatus communication | 2 | partial | 7/10 | Cclaimed | |
A condition-based workflow engine automates the toil — updates, reminders, field changes — triggered by incident events C Workflows | sre | Automation runbooks — stories about automation runbooks in this arenaAutomation runbooks | 2 | partial | 6/10 | Cclaimed | |
Do everything through the API that I can do in the UI G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | partial | 6/10 | Tprobed | |
I get reliability analytics — MTTA/MTTR trends, incident load, on-call health — to see whether we are actually improving C Metrics | engineering leader | Analytics reliability — stories about analytics reliability in this arenaAnalytics reliability | 2 | partial | 6/10 | Cclaimed | |
The platform integrates with the tools around the incident — Jira, Slack, Teams, Zoom, GitHub — so state flows both ways C Workflow tools | sre | Integrations observability — stories about integrations observability in this arenaIntegrations observability | 2 | partial | 6/10 | Cclaimed | |
Follow-up actions from incidents are tracked to completion and sync to our issue tracker C Follow ups | engineering leader | Postmortems learning — stories about postmortems learning in this arenaPostmortems learning | 2 | partial | 5/10 | Cclaimed | |
A full mobile app lets me acknowledge, escalate, and resolve from my phone at 3am C Mobile | on-call engineer | Mobile experience — stories about mobile experience in this arenaMobile experience | 2 | none | 0/10 | ||
Pages reach me over the channels I choose — push, SMS, phone call, and email — with per-channel notification rules C Paging | on-call engineer | Alerting escalation — stories about alerting escalation in this arenaAlerting escalation | 2 | none | 0/10 | ||
Perform bulk operations across many items at once G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | none | 0/10 | ||
Runbooks attach to incidents and their steps can trigger automatically — creating channels, assigning tasks, running diagnostics C Runbooks | sre | Automation runbooks — stories about automation runbooks in this arenaAutomation runbooks | 2 | none | 0/10 | ||
Schedule recurring jobs or workflows G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | none | 0/10 | ||
Take an override, swap a shift, or request coverage without an admin rebuilding the schedule C Schedules | on-call engineer | On call scheduling — stories about on call scheduling in this arenaOn call scheduling | 2 | none | 0/10 | ||
Choose where my data is stored (region/residency) G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Control data retention and deletion G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Opt out of telemetry and usage tracking G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Read the product's source under an open license G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | n/a | untested | none yet | |
Run private or internal status pages with access control for customer-specific or employee-only audiences G Status pages | engineering leader | Status communication — stories about status communication in this arenaStatus communication | 1 | partial | 6/10 | Cclaimed | |
Internal stakeholders get structured incident updates they can subscribe to, without joining the war room C Communications | engineering leader | Incident response — stories about incident response in this arenaIncident response | 1 | partial | 5/10 | Cclaimed | |
My shifts sync to my personal calendar via a feed so I always know when I'm on the hook C Quality of life | on-call engineer | On call scheduling — stories about on call scheduling in this arenaOn call scheduling | 1 | none | 0/10 | ||
Version, review, and roll back my automations G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 1 | none | 0/10 | ||
Incidents carry defined roles (commander, comms lead) and task checklists so response stays coordinated under pressure C Coordination | engineering leader | Incident response — stories about incident response in this arenaIncident response | 1 | none | untested | none yet |
Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 35 stories with headroom
What would move incident.io’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.
Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools
nonemoves agent-readyimpact 45
All MCP evidence describes incident.io publishing its own remote MCP server so external AI assistants can query incident.io's data — the reverse of what this story asks (the product itself consuming/plugging in third-party MCP servers to gain their tools).
Integrations observability — stories about integrations observability in this arenaFirst-party integrations cover my observability stack — Datadog, Grafana, Prometheus, CloudWatch, Sentry — with documented setup
nonemoves PA Scoreimpact 30
Evidence only mentions generic claims like '40 alert sources ready to go' and 'Configure alerts from your observability tools' without naming or documenting setup for Datadog, Grafana, Prometheus, CloudWatch, or Sentry specifically.
Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models
nonemoves PA Scoreimpact 30
No evidence in the pack addresses any data usage, AI training opt-out, or privacy policy commitments regarding customer/incident data being used to train AI models; the docs cover AI features (Investigations, Suggestions, Scribe, MCP) but never mention data-training exclusion or opt-out controls.
Agenticness — how well agents can access and operate the productUse an official CLI
nonemoves agent-readyimpact 30
Missing: any mention of an incident.io CLI binary/package, its installation, or command-line usage documentation.
Agenticness — how well agents can access and operate the productIssue scoped/least-privilege API credentials for an agent
partialq3/10moves agent-readyimpact 21
Missing: explicit API-key permission/scope configuration UI or docs, role-based least-privilege key issuance, confirmation that MCP OAuth tokens can be scoped down per-agent.
Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy
partialq3/10moves API qualityimpact 21
Missing: explicit deprecation policy docs, version sunset timelines, migration guides between API versions.
Automation depth — how much of the product can run unattendedPerform bulk operations across many items at once
nonemoves PA Scoreimpact 20
The evidence pack shows a REST API, webhooks, and an MCP server for querying incidents/alerts/on-call data, but nothing describes bulk/batch operations (e.g., updating many incidents, alerts, or schedules in one call) that an AI agent could invoke at scale.
Automation depth — how much of the product can run unattendedSchedule recurring jobs or workflows
nonemoves PA Scoreimpact 20
incident.io's Workflows feature (docs-9) is event-triggered (e.g., publish to status page when an incident updates) and on-call 'Schedules' (docs-24, docs-42) refer to rotation calendars, not recurring automation jobs.
Showing the top 8 of 35 — every none/partial verdict in the story verdicts table is headroom.
Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.
Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map17 surfaces · 36 covered stories
Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.
API reference13 stories
- Point an agent at llms.txt or agent-oriented docs
- Run the product headlessly / in CI for automation
- Drive the product through a documented public API
- Issue scoped/least-privilege API credentials for an agent
- Build against official SDKs
- Explore an interactive API reference with runnable examples
- Download a machine-readable API spec (OpenAPI or equivalent)
- Rely on versioned APIs with a documented deprecation policy
- My agent can acknowledge, escalate, and resolve incidents end to end through a documented API or MCP connection — no dashboard in the loop
- The platform integrates with the tools around the incident — Jira, Slack, Teams, Zoom, GitHub — so state flows both ways
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
- Follow-up actions from incidents are tracked to completion and sync to our issue tracker
AI docs12 stories
- Connect an agent via an official MCP server
- Issue scoped/least-privilege API credentials for an agent
- Get AI-generated insights and suggestions from my data inside the product
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- Test against a sandbox environment without touching production data
- My agent can acknowledge, escalate, and resolve incidents end to end through a documented API or MCP connection — no dashboard in the loop
- AI drafts the postmortem from the incident record — timeline, contributing factors, follow-ups — ready for human review
- AI writes the incident as it happens — live summaries, drafted updates, and scribed call notes — so responders respond instead of typing
- Internal stakeholders get structured incident updates they can subscribe to, without joining the war room
- Declare and run an incident from chat — Slack or Teams — with channels, roles, and updates created for me
- Do everything through the API that I can do in the UI
Integrations docs8 stories
- Run the product headlessly / in CI for automation
- Subscribe to events via webhooks
- Define rules that trigger actions automatically on events
- A condition-based workflow engine automates the toil — updates, reminders, field changes — triggered by incident events
- The platform integrates with the tools around the incident — Jira, Slack, Teams, Zoom, GitHub — so state flows both ways
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
- Follow-up actions from incidents are tracked to completion and sync to our issue tracker
Status pages docs7 stories
- Set up automations that run autonomously in the background
- Define rules that trigger actions automatically on events
- A condition-based workflow engine automates the toil — updates, reminders, field changes — triggered by incident events
- Internal stakeholders get structured incident updates they can subscribe to, without joining the war room
- Do everything through the API that I can do in the UI
- Run private or internal status pages with access control for customer-specific or employee-only audiences
- Publish a hosted public status page — custom domain, subscriber notifications — driven from incident state
Incidents docs6 stories
- Test against a sandbox environment without touching production data
- AI drafts the postmortem from the incident record — timeline, contributing factors, follow-ups — ready for human review
- Declare and run an incident from chat — Slack or Teams — with channels, roles, and updates created for me
- The incident timeline is captured automatically — alerts, actions, and chat decisions — and I can edit or annotate it afterwards
- The platform integrates with the tools around the incident — Jira, Slack, Teams, Zoom, GitHub — so state flows both ways
- Postmortems follow a real workflow — templates, drafting from the timeline, review, and publication
Investigations docs6 stories
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- An AI investigator digs into the probable cause — correlating changes, telemetry, and similar past incidents — before a human even asks
- AI drafts the postmortem from the incident record — timeline, contributing factors, follow-ups — ready for human review
- The platform integrates with the tools around the incident — Jira, Slack, Teams, Zoom, GitHub — so state flows both ways
On call docs5 stories
- Escalation policies walk unacknowledged pages through multiple steps — delays, fallback responders, and repeat rounds — until someone acknowledges
- Alerts from my monitoring tools are ingested through documented sources and routed to the right team by conditions I define
- Define rules that trigger actions automatically on events
- The incident timeline is captured automatically — alerts, actions, and chat decisions — and I can edit or annotate it afterwards
- Build on-call schedules with rotations, layers, time zones, and round-robin coverage that match how my teams actually work
Post incident docs5 stories
- Delegate tasks to a built-in AI assistant inside the product
- AI drafts the postmortem from the incident record — timeline, contributing factors, follow-ups — ready for human review
- A condition-based workflow engine automates the toil — updates, reminders, field changes — triggered by incident events
- Follow-up actions from incidents are tracked to completion and sync to our issue tracker
- Postmortems follow a real workflow — templates, drafting from the timeline, review, and publication
Investigations docs4 stories
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- An AI investigator digs into the probable cause — correlating changes, telemetry, and similar past incidents — before a human even asks
Alerts docs3 stories
Changelog docs3 stories
Status pages docs3 stories
- Internal stakeholders get structured incident updates they can subscribe to, without joining the war room
- Run private or internal status pages with access control for customer-specific or employee-only audiences
- Publish a hosted public status page — custom domain, subscriber notifications — driven from incident state
llms.txt2 stories
OpenAPI spec2 stories
Insights docs2 stories
On call docs2 stories
Probe proofs — replayable recordings from the probe harnessProbe proofs
Replayable recordings from our probe harness — see the Prove-It protocol to submit one.
$curl -si -X POST https://mcp.incident.io/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'reproduced$ curl -si -X POST https://mcp.incident.io/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' HTTP/2 401 cache-control: no-cache, private, max-age=0 content-security-policy: report-uri https://o494704.ingest.sentry.io/api/5566257/security/?sentry_[redacted]=ed63d41bdbf74c6d92688c7ee410e72f; img-src 'self' data: blob: https://avataaars.io https://platform.slack-edge.com https://images.unsplash.com https://avatars.slack-edge.com https://a.slack-edge.com https://emoji.slack-edge.com https://avatars.githubusercontent.com https://avatar-management--avatars.us-west-2.prod.public.atl-paas.net https://site-admin-avatar-cdn.prod.public.atl-paas.net https://secure.gravatar.com https://uploads.linear.app https://public.linear.app https://wp.com https://*.wp.com https://*.atlassian.net https://storage.googleapis.com https://incident.io https://*.googleusercontent.com https://cdn.sanity.io https://secure.aadcdn.microsoftonline-p.com https://aadcdn.msftauthimages.net https://aadcdn.msauthimages.net https://merge-api-public.s3.amazonaws.com assets.incident.io; object-src 'none'; script-src 'self' 'wasm-unsafe-eval' *.sentry.io https://js.stripe.com https://embed.explo.co/ https://cdn.merge.dev https://evs.seg.incident.io/ assets.incident.io; style-src 'self' 'unsafe-inline' https://maxcdn.bootstrapcdn.com https://embed.explo.co/ assets.incident.io; font-src data: 'self' https://maxcdn.bootstrapcdn.com assets.incident.io; frame-src 'self' blob: https://js.stripe.com https://hooks.stripe.com https://loom.com https://www.loom.com https://calendly.com/ https://app.svix.com/ https://app.explo.co/ https://inquiry.withpersona.com/ https://cdn.merge.dev; connect-src 'self' *.sentry.io https://api.stripe.com https://app.launchdarkly.com https://*.launchdarkly.com https://storage.googleapis.com/ https://api.explo.co/ https://embed.explo.co/ https://incident.io https://status.incident.io https://res.cdn.office.net wss://collaboration.incident.io wss://collaboration.staging.incident.io https://api.merge.dev https://cdn.merge.dev https://evs.seg.incident.io/ https://api.seg.incident.io/ assets.incident.io; base-uri 'none'; default-src 'self'; frame-ancestors 'self' https://teams.microsoft.com https://*.teams.microsoft.com https://teams.cloud.microsoft; media-src 'self' blob: https://storage.googleapis.com; content-type: text/plain; charset=utf-8 expires: Thu, 01 Jan 1970 00:00:00 UTC permissions-policy: clipboard-write=(self "https://app.svix.com") pragma: no-cache referrer-policy: strict-origin-when-cross-origin strict-transport-security: max-age=315360000; includeSubDomains vary: * vary: Accept-Encoding www-authenticate: Bearer resource_metadata="https://mcp.incident.io/mcp/.well-known/oauth-protected-resource" x-accel-expires: 0 x-content-type-options: nosniff x-frame-options: DENY x-request-id: 3vii5cjT x-trace-id: 39329d226988090d5685c6ce59fcf276 x-xss-protection: 1; mode=block date: Mon, 07 Sep 2026 05:11:55 GMT content-length: 16 x-inc-srv: mcp via: 1.1 google alt-svc: h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 no bearer [redacted]
$curl -s https://docs.incident.io/openapi/tags/incidents-v2.json | head -8reproduced$ curl -s https://docs.incident.io/openapi/tags/incidents-v2.json | head -8
{
"openapi": "3.0.3",
"info": {
"description": "This is the API reference for incident.io.\n\nIt documents available API endpoints, provides examples of how to use it, and\ninstructions around things like authentication and error handling.\n\nThe API is hosted at:\n\n- https://api.incident.io/\n\nAnd you will need to create an API [redacted] via your [incident.io\ndashboard](https://app.incident.io/settings/api-[redacted]s) to make requests.\n\n# Making requests\n\nHere are the [redacted] concepts required to make requests to the incident.io API.\n\n## Authentication\n\nFor all requests made to the incident.io API, you'll need an API [redacted].\n\nTo create an API [redacted], head to the incident dashboard and visit [API\n[redacted]s](https://app.incident.io/settings/api-[redacted]s). When you create the [redacted], you'll be able to choose what actions it\ncan take for your account: choose carefully, as those roles can only be set\nwhen you first create the [redacted]. We'll only show you the [redacted] once, so make sure\nyou store it somewhere safe.\n\nAPI [redacted]s are global to your incident.io account, and can be managed by anyone\nwho has the right permissions. We display the user that created the API [redacted],\nand the API [redacted] will remain valid if that user becomes deactivated.\n\nOnce you have the [redacted], you should make requests to the API that set the\n`Authorization` request header using a \"Bearer\" authentication scheme:\n\n```\nAuthorization: Bearer <YOUR_API_[redacted]>\n```\n\n## Rate Limits\n\nThe incident.io API enforces rate limits to ensure consistent performance for all users.\n\nThe default rate limit is 1200 requests/minute per API [redacted]. This limit applies to most endpoints across the API.\n\nLimits are [redacted] buckets that refill continuously rather than resetting on a fixed window boundary. The default\nbucket holds 1200 requests and refills at 20 per second, so you can burst up to the full bucket and then sustain\n20 requests/second indefinitely. There is no boundary at which your quota resets to full in one step.\n\nSome endpoints have lower rate limits, particularly those that interact with external third-party systems that impose\ntheir own limitations. These specific limits vary by endpoint.\n\n### Rate limit headers\n\nResponses to requests authenticated with an API [redacted] carry your current allowance, so you can pace yourself rather\nthan waiting to be throttled:\n\n```\nX-RateLimit-Limit: 60, 1200;window=60, 60;window=60\nX-RateLimit-Remaining: 59\nX-RateLimit-Used: 1\nX-RateLimit-Reset: 1785173199\n```\n\n| Header | Meaning |\n| --- | --- |\n| `X-RateLimit-Limit` | The quota that binds this request, followed by every limit that applied and the window it applies over |\n| `X-RateLimit-Remaining` | Requests you can make right now against the binding limit |\n| `X-RateLimit-Used` | Requests you have spent against it |\n| `X-RateLimit-Reset` | Unix timestamp (seconds) at which that limit will be back to full |\n\nMore than one limit can apply to a request: your API [redacted]'s overall limit, and for some endpoints a lower limit of\ntheir own. `X-RateLimit-Limit` lists all of them, each with its window, so `1200;window=60` means 1200 requests per\nminute. Because our limits refill continuously rather than resetting on a boundary, that window is what tells you\nthe rate you can sustain: 1200 per 60 seconds is 20 requests/second indefinitely.\n\n`Remaining`, `Used` and `Reset` describe whichever limit has the least allowance left, since that is the one you\nwill hit first.\n\n`X-RateLimit-Remaining` may lag by a small number of requests under high concurrency, and can move by more than the\nrequests you made, because limits scoped to your whole organisation are shared with your other API [redacted]s.\n\nHeaders are omitted rather than guessed if we cannot determine your allowance for a request.\n\n### Exceeding a rate limit\n\nWhen you exceed a rate limit the API responds with `429 Too Many Requests` and a `Retry-After` header giving the\nnumber of seconds to wait:\n\n```\nX-RateLimit-Limit: 1200, 1200;window=60\nX-RateLimit-Remaining: 0\nX-RateLimit-Used: 1200\nX-RateLimit-Reset: 1785173199\nRetry-After: 1\n```\n\nPrefer `Retry-After` over `X-RateLimit-Reset` when deciding how long to back off. `Retry-After` is when a single\nrequest will succeed; `X-RateLimit-Reset` is the later point at which your whole allowance has returned. It is a\nduration rather than a timestamp, so it does not depend on your clock agreeing with ours.\n\nThe 429 also carries a JSON body with the same information:\n\n```json\n{\n \"type\": \"too_many_requests\",\n \"status\": 429,\n \"request_id\": \"b839a403-7704-41c1-bf6a-39a2d68caefa\",\n \"rate_limit\": {\n \"name\": \"api_[redacted]_name\",\n \"limit\": 1200,\n \"remaining\": 0,\n \"retry_after\": \"2025-04-17T11:17:18Z\"\n },\n \"errors\": [\n {\n \"code\": \"too_many_requests\",\n \"message\": \"Too many requests hit the API too quickly. We recommend an exponential backoff of your requests.\"\n }\n ]\n}\n```\n\nThe response includes:\n* The name of the API [redacted] (`name`)\n* The bucket limit (`limit`)\n* The number of requests remaining (`remaining`)\n* When you can retry requests (`retry_after`), as an RFC3339 timestamp\n\n## Errors\n\nWe use standard HTTP response codes to indicate the status or failure of API\nrequests.\n\nThe API response body will be JSON, and contain more detailed information on the\nnature of the error.\n\nAn example error when a request is made without an [redacted] \"type\": \"authentication_error\",\n \"status\": 401,\n \"request_id\": \"8e3cc412-b49d-4957-9073-2c19d2c61804\",\n \"errors\": [\n {\n \"code\": \"missing_authorization_material\",\n \"message\": \"No authorization material provided in request\"\n }\n ]\n}\n```\n\nNote that the error:\n\n- Contains the HTTP status (`401`)\n- References the type of error (`authentication_error`)\n- Includes a `request_id` that can be provided to incident.io support to help\n\tdebug questions with your API request\n- Provides a list of individual errors, which go into detail about why the error\n\toccurred\n\nThe most common error will be a 422 Validation Error, which is returned when the\nrequest was rejected due to failing validations.\n\nThese errors look like this:\n\n```json\n{\n \"type\": \"validation_error\",\n \"status\": 422,\n \"request_id\": \"631766c4-4afd-4803-997c-cd700928fa4b\",\n \"errors\": [\n {\n \"code\": \"is_required\",\n \"message\": \"A severity is required to open an incident\",\n \"source\": {\n \"field\": \"severity_id\"\n }\n }\n ]\n}\n```\n\nThis error is caused by not providing a severity identifier, which should be at\nthe `severity_id` field of the request payload. Errors like these can be mapped to\nforms, should you be integrating with the API from a user-interface.\n\n## Compatibility\n\nWe won't make breaking changes to existing API services or endpoints, but will\nexpect integrators to upgrade themselves to the latest API endpoints within 3\nmonths of us deprecating the old service.\n\nWe will make changes that are considered backwards compatible, which include:\n\n- Adding new API endpoints and services\n- Adding new properties to responses from existing API endpoints\n- Reordering properties returned from existing API endpoints\n- Adding optional request parameters to existing API endpoints\n- Altering the format or length of IDs\n- Adding new values to enums\n\nIt is important that clients are robust to these changes, to ensure reliable\nintegrations.\n\nAs an example, if you are generating a client using an openapi-generator, ensure\nthe generated client is configured to support unknown enum values, often\nconfigured via the `enumUnknownDefaultCase` parameter.\n\nWhen breaking changes are unavoidable, we'll create a new service version on a\nseparate path, and run them in parallel.\n\nFor example:\n\n- https://api.incident.io/v1/incidents\n- https://api.incident.io/v2/incidents\n\nFor any questions, email support@incident.io.\n",
"title": "incident.io",
"version": "1.0.0"
},
"servers": [
Business model
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pricing ↗Score trend
How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.
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Agent surface uptime MCP 100% · llms.txt 100% (30d, checked every 6h since Sep 8 '26)
