Cotool website screenshot

Cotool

Cotool is an AI platform for the defensive security "blue team" — AI agents that scale detection, response, and threat hunting across an organization's security stack. Its three products, Detect, Respond, and Hunt, let teams author detections from natural-language descriptions, automate alert response and playbook execution with human-in-the-loop controls, and monitor threat intelligence for relevance and coverage gaps. Cotool's stated mission is to "scale defensive security with tokens," giving defenders machine-speed operational advantages instead of being limited by headcount, improving coverage and cutting mean-time-to-respond (MTTR). Cotool is a San Francisco company backed by Andreessen Horowitz (a16z), Y Combinator, WndrCo, and Homebrew. As of this profile it publishes a product and marketing site only — no public API, developer documentation, SDK, or MCP server was found.

Cotool is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Cybersecurity, Security Operations, and Threat Detection.

Cotool’s developer surface includes engineering blog and 9 more developer resources.

🌐 Visit website📡 Profile data on GitHub
10.2/100 minimal ▬ flat Agent 9/100 agent aware Front door AI 4/6 moderate saas Full breakdown ↓
scored 2026-10-17 · rubric v0.24.0
0 APIs 1 MCP Servers
CompanyArtificial IntelligenceCybersecuritySecurity OperationsThreat DetectionIncident ResponseThreat HuntingBlue TeamSOC Automation

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-10-17 · rubric v0.24.0
Composite quality — 10.2/100 · minimal
Contract Quality 0.0 / 21
Developer Ergonomics 0.4 / 17
Access Clarity 3.6 / 17
Operational Transparency 0.0 / 11
Contract Governance 0.0 / 10
Discoverability 5.0 / 9
Regulatory Posture 1.9 / 15
Agent readiness — 9/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 10
Documented Reversibility 0 / 6
MCP Server 12 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3
A2A Agent Card 0 / 8
Dry-Run / Simulate Mode 0 / 4
Delegated User Identity 0 / 6
Protected Resource Metadata 0 / 5
Registration Without a Human 0 / 6
Agentic Commerce Well-Known Document 0 / 5
Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.
The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/cotool: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Cotool MCP Server

Remote MCP server at docs.cotool.ai over HTTP.

MCP SERVER

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Cotool Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

WellKnown
WellKnown
 LLMsTxt
LLMsTxt

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity
DomainSecurity

Commercial 2

Pricing, plans, and the legal terms of use

PrivacyPolicy
PrivacyPolicy
 TermsOfService
TermsOfService

Company 5

The organization behind the API

Website
Website
 About
About
 Blog
Blog
 LinkedIn
LinkedIn
 Twitter
Twitter

Source (apis.yml)

apis.yml Raw ↑ 
aid: cotool
name: Cotool
description: Cotool is an AI platform for the defensive security "blue team" — AI agents that scale detection, response, and
  threat hunting across an organization's security stack. Its three products, Detect, Respond, and Hunt, let teams author
  detections from natural-language descriptions, automate alert response and playbook execution with human-in-the-loop controls,
  and monitor threat intelligence for relevance and coverage gaps. Cotool's stated mission is to "scale defensive security
  with tokens," giving defenders machine-speed operational advantages instead of being limited by headcount, improving coverage
  and cutting mean-time-to-respond (MTTR). Cotool is a San Francisco company backed by Andreessen Horowitz (a16z), Y Combinator,
  WndrCo, and Homebrew. As of this profile it publishes a product and marketing site only — no public API, developer documentation,
  SDK, or MCP server was found.
url: https://raw.githubusercontent.com/api-evangelist/cotool/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- homebrew
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
image: https://www.cotool.ai/images/og.jpg
tags:
- Company
- Artificial Intelligence
- Cybersecurity
- Security Operations
- Threat Detection
- Incident Response
- Threat Hunting
- Blue Team
- SOC Automation
tags_raw:
- Company
- AI
- Cybersecurity
- Security Operations
- Threat Detection
- Incident Response
- Threat Hunting
- Blue Team
- SOC Automation
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.cotool.ai
- type: About
  url: https://www.cotool.ai/about
- type: Blog
  url: https://www.cotool.ai/blog
- type: PrivacyPolicy
  url: https://www.cotool.ai/privacy-policy
- type: TermsOfService
  url: https://www.cotool.ai/license
- type: LinkedIn
  url: https://www.linkedin.com/company/cotool-ai
- type: Twitter
  url: https://x.com/cotoolai
- type: DomainSecurity
  url: security/cotool-domain-security.yml
- type: WellKnown
  url: well-known/cotool-well-known.yml
- type: LLMsTxt
  url: llms/cotool-llms.txt
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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