AI Company Profile

Anthropic

Claude Code is Anthropic's agentic coding tool for working with codebases from the terminal and connected developer workflows.

Primary category
AI Coding Tools, AI Developer Tools
Audience
AI Coding Tool Users, Developers, Engineering Teams
Founder/team
Unknown
Funding
Unknown
Linked launches
18 launches
Linked tools
6 tools
Verification
Unknown
Source links
2

Company Overview

Anthropic is tracked in the Kingy AI company directory because it is connected to public AI launch and tool records. Claude Code is Anthropic's agentic coding tool for working with codebases from the terminal and connected developer workflows.

The current public graph connects 18 launches and 6 tools to Anthropic. That turns this profile into a working research hub: use it to move from the company to its product surface, then into dated launch records with source checks, verification status, and related Kingy AI context.

For AI Coding Tool Users, Developers, Engineering Teams, the useful question is not only what Anthropic says about itself. The useful question is what the launch pattern shows: which categories the company is active in, which tools have durable profiles, whether pricing and demos are clear, and whether the source trail is strong enough for deeper editorial or creator coverage.

AI Product Evidence

This company profile is backed by a linked AI tool record: Claude Code is Anthropic's agentic coding tool for working with codebases from the terminal and connected developer workflows.

Research Notes

When reviewing Anthropic, check the official product surface, docs, demos, pricing, model or API pages, and linked Kingy AI launch records before relying on claims for buying, writing, comparison, or creator-coverage decisions.

Source-Backed Profile Notes

This profile is checked against public source links where available. Official product pages, documentation, model pages, pricing pages, launch announcements, and verified company pages should carry more weight than social posts or unsourced summaries.

Market Position

Kingy AI currently classifies Anthropic around AI Coding Tools, AI Developer Tools. Those categories are not meant to be a marketing slogan; they are a practical way to understand where the company shows up in the launch database and how it may intersect with product strategy, adoption, search demand, and creator education.

Audience Fit

This profile is especially useful for AI Coding Tool Users, Developers, Engineering Teams. A complete read should start with the company snapshot, continue through the linked tools and launch timeline, and end with the source panel so claims can be checked before a buying decision, article, comparison, or video brief.

Latest Tracked Move

The most recent linked launch for Anthropic is Anthropic launches Claude Corps fellowship for early-career AI work from June 11, 2026. Anthropic launched Claude Corps, a paid 12-month fellowship that it says will train and place 1,000 early-career workers with mission-driven nonprofits across three cohorts. CodePath employs the fellows and Social Finance helps administer capital and evaluation. The first cohort is scheduled to begin October 19, 2026;…

Read the latest launch record

Product Surface

One linked tool profile is Claude. Support conversational research, analysis, drafting, coding and sustained knowledge work across web, desktop and mobile. The tool profile is where Kingy AI keeps product-level details such as what it does, pricing clarity, API availability, alternatives, related launches, and source-backed evaluation notes.

Open linked tool profile

Launch Graph And Timeline

The launch graph is the most important part of this page. It shows how Anthropic appears through dated AI product events instead of a generic company description. Each launch record can include category, audience, source links, pricing notes, demo signals, scoring, and a best-next-link path for deeper research.

  1. Anthropic launched Claude Corps, a paid 12-month fellowship that it says will train and place 1,000 early-career workers with mission-driven nonprofits across three cohorts. CodePath employs the fellows and Social Finance helps administer capital and evaluation.…

  2. Anthropic announced Claude Fable 5 alongside Claude Mythos 5 as a Mythos-class model release for hard knowledge work and coding tasks.

  3. Anthropic announced the retirement of claude-opus-4-1-20250805 on the Claude API for August 5, 2026 and recommends claude-opus-4-8. Anthropic notes that partner-platform schedules can differ from its operated API surfaces.

  4. Anthropic released Claude Opus 4.8 with improved coding, agentic task performance, professional work quality, effort controls, and Claude Code dynamic workflows.

  5. Anthropic released Claude Opus 4.7 as a frontier Claude update relevant to demanding coding, reasoning, and agentic tasks.

  6. With the April 16 launch of Claude Opus 4.7, Anthropic introduced a breaking API change: requests setting non-default temperature, top_p, or top_k values return HTTP 400. Anthropic recommends omitting these parameters and using prompting to guide…

  7. Anthropic released Claude Opus 4.5 as a frontier Claude model update with emphasis on advanced reasoning, coding, and agentic work.

  8. Anthropic released Claude Sonnet 4.5, positioning it as a top model for coding, complex agents, and computer use while also launching related Claude Code and Agent SDK upgrades.

  9. Anthropic introduced the Claude Agent SDK, described as the infrastructure used to build Claude Code and now available for developers building agents.

  10. Claude Opus 4.1

    Anthropic released Claude Opus 4.1 as an upgrade to Opus 4 for agentic tasks, real-world coding, and reasoning.

  11. Introducing Claude 4

    Anthropic introduced Claude Opus 4 and Claude Sonnet 4, plus Claude Code general availability and new API capabilities for agents.

  12. Anthropic introduced web search on the API so developers can build Claude applications that retrieve and cite current web information.

  13. Anthropic added web search to Claude, enabling current web retrieval, source citations, and source-backed answers inside Claude conversations.

  14. Anthropic launched Claude 3.7 Sonnet as a hybrid reasoning model and introduced Claude Code, an agentic command-line coding tool, in research preview.

  15. Anthropic open-sourced the Model Context Protocol as a standard for connecting AI assistants to external data sources and tools.

  16. Anthropic introduced computer use in public beta alongside an upgraded Claude 3.5 Sonnet and the new Claude 3.5 Haiku model.

  17. Anthropic launched Projects in Claude.ai, letting Pro and Team users organize chats and knowledge into persistent workspaces.

  18. Claude 3.5 Sonnet

    Anthropic launched Claude 3.5 Sonnet, the first release in the Claude 3.5 model family, with strong intelligence, coding, vision, and API availability.

Tool Portfolio

The tool portfolio section turns the company profile into a navigable product map. For Anthropic, Kingy AI currently links 6 tools that can be reviewed separately for pricing, demos, use cases, alternatives, related launches, and source-backed notes.

AI Productivity Tools

Claude

Support conversational research, analysis, drafting, coding and sustained knowledge work across web, desktop and mobile.

Pricing
Free access plus Pro, Max and Team subscriptions; Anthropic API usage is metered and billed separately.
API
yes
AI Agents, AI Developer Tools, AI Infrastructure

Claude Agent SDK

The Claude Agent SDK lets developers build agents using Claude Code-style tools, permissions, sessions, and orchestration patterns.

Pricing
SDK use is governed by current Claude API model pricing and any infrastructure or tool costs in the implementation.
API
yes
AI Browser Agents

Claude API

The Claude API is Anthropic's REST API for programmatic access to Claude models, including messages, batch processing, token counting, tools, and managed-agent workflows.

Pricing
Usage is billed at model-specific rates, with separate pricing for some features; current prices are listed in Anthropic's official documentation.
API
yes
AI Developer Tools

Claude Code

Claude Code is Anthropic's agentic coding tool for working with codebases from the terminal and connected developer workflows.

Pricing
Access depends on Anthropic Claude plans and API or product terms; verify current limits on official pages.
API
yes
AI Coding Tools, AI Models

Claude Fable 5: Pricing, Safeguards, Coding Fit, and Limits

Claude Fable 5 is Anthropic’s safeguarded Mythos-class model for long-running coding, research, document analysis and other multi-stage knowledge work.

Pricing
Anthropic lists $10 per million input tokens and $50 per million output tokens, with a 90% prompt-caching input discount; confirm current plan and regional terms.
API
yes
AI Infrastructure

Model Context Protocol

Anthropic open-sourced the Model Context Protocol as a standard for connecting AI assistants to external data sources and tools.

Pricing
Open standard and SDK ecosystem; implementation costs depend on hosting, clients, servers, and platform usage.
API
yes

Launch Record Cards

Use these cards when you want the shorter scan view: category, launch date, scores, open/API/free-plan signals, and the path into the full launch profile.

AI Productivity Tools

Anthropic launches Claude Corps fellowship for early-career AI work

Anthropic launched Claude Corps, a paid 12-month fellowship that it says will train and place 1,000 early-career workers with mission-driven nonprofits across three cohorts. CodePath employs the fellows…

Recheck due Free: No API: No Open: No
Clear use case

Claude Corps should be evaluated as workforce and nonprofit capacity-building, not as a Claude feature. Its scale, paid structure, training time and host support…

AI Coding Tools

Claude Fable 5 and Mythos-class model launch

Anthropic announced Claude Fable 5 alongside Claude Mythos 5 as a Mythos-class model release for hard knowledge work and coding tasks.

Recheck due Free: Unknown API: Yes Open: No
Clear use caseVideo demoTraction signal
Launch readiness
8.4 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-07-10.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic announced Claude Fable 5 alongside Claude Mythos 5, a Mythos-class release for hard knowledge work and coding that drew same-day coverage from TechCrunch…

AI Agents

Anthropic retired Claude Opus 4.1 on August 5, 2026

Anthropic announced the retirement of claude-opus-4-1-20250805 on the Claude API for August 5, 2026 and recommends claude-opus-4-8. Anthropic notes that partner-platform schedules can differ from its operated API…

Source-verified Free: No API: Yes Open: No
Clear use caseDeveloper-friendly

Treat August 5 as a model retirement deadline, not a product launch or a blind model-ID replacement. Inventory traffic by provider, confirm which schedule…

AI Agents

Introducing Claude Opus 4.8

Anthropic released Claude Opus 4.8 with improved coding, agentic task performance, professional work quality, effort controls, and Claude Code dynamic workflows.

Recheck due Free: No API: Yes Open: No
Clear use caseVideo demoBusiness-friendlyDeveloper-friendly
Launch readiness
7.9 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic released Claude Opus 4.8 with improved coding, agentic task performance, effort controls, and Claude Code dynamic workflows, priced at $5 per million input…

AI Agents

Claude Opus 4.7 launches as an Anthropic frontier model update for agent work

Anthropic released Claude Opus 4.7 as a frontier Claude update relevant to demanding coding, reasoning, and agentic tasks.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendly

A frontier Claude release is relevant to the agent market because high-capability models determine what long-running agents can reliably complete.

AI Developer Tools

Anthropic removes non-default sampling controls starting with Claude Opus 4.7

With the April 16 launch of Claude Opus 4.7, Anthropic introduced a breaking API change: requests setting non-default temperature, top_p, or top_k values return HTTP 400. Anthropic recommends…

Source-verified Free: Yes API: Yes Open: No
Clear use caseDeveloper-friendly

This is a request-compatibility break for teams that carry sampling overrides forward between Claude versions. Remove non-default temperature, top_p and top_k values before moving…

AI Agents

Claude Opus 4.5 launches as Anthropic’s frontier agentic model update

Anthropic released Claude Opus 4.5 as a frontier Claude model update with emphasis on advanced reasoning, coding, and agentic work.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendly

A relevant model launch because the strongest Claude tier often becomes the default choice for demanding agent tasks.

AI Agents

Claude Sonnet 4.5 launches with major coding-agent and computer-use gains

Anthropic released Claude Sonnet 4.5, positioning it as a top model for coding, complex agents, and computer use while also launching related Claude Code and Agent SDK upgrades.

Recheck due Free: No API: Yes Open: No
Clear use caseDeveloper-friendly

A high-signal model release for agents because Anthropic explicitly tied it to coding, computer use, and the Claude Agent SDK.

AI Agents

Claude Agent SDK opens Anthropic’s Claude Code agent infrastructure to developers

Anthropic introduced the Claude Agent SDK, described as the infrastructure used to build Claude Code and now available for developers building agents.

Recheck due Free: No API: Yes Open: No
Clear use case

Important because it productizes the agent infrastructure behind Claude Code rather than leaving teams to recreate orchestration patterns.

AI Coding Tools

Claude Opus 4.1

Anthropic released Claude Opus 4.1 as an upgrade to Opus 4 for agentic tasks, real-world coding, and reasoning.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.4 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic released Claude Opus 4.1 as an upgrade to Opus 4 for agentic tasks, real-world coding, and reasoning, at the same pricing as its…

AI Coding Tools

Introducing Claude 4

Anthropic introduced Claude Opus 4 and Claude Sonnet 4, plus Claude Code general availability and new API capabilities for agents.

Recheck due Free: Yes API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal

A top-tier launch for this hub because Claude 4 tied frontier models directly to developer-agent adoption.

AI Infrastructure

Introducing web search on the Anthropic API

Anthropic introduced web search on the API so developers can build Claude applications that retrieve and cite current web information.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.3 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic introduced web search on the Claude API, letting developers build applications that retrieve and cite current web information as a first-party tool, priced…

AI Search Tools

Claude can now search the web

Anthropic added web search to Claude, enabling current web retrieval, source citations, and source-backed answers inside Claude conversations.

Recheck due Free: Yes API: No Open: No
Clear use caseBeginner-friendlyBusiness-friendlyTraction signal
Launch readiness
6.6 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic added web search to Claude, enabling current web retrieval, source citations, and source-backed answers inside conversations (claude.com). It closes a gap that had…

AI Coding Tools

Claude 3.7 Sonnet and Claude Code

Anthropic launched Claude 3.7 Sonnet as a hybrid reasoning model and introduced Claude Code, an agentic command-line coding tool, in research preview.

Recheck due Free: Yes API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.2 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic launched Claude 3.7 Sonnet as a hybrid reasoning model and introduced Claude Code, an agentic command-line coding tool, in research preview (anthropic.com). The…

AI Infrastructure

Introducing the Model Context Protocol

Anthropic open-sourced the Model Context Protocol as a standard for connecting AI assistants to external data sources and tools.

Recheck due Free: Yes API: Yes Open: Yes
Clear use caseBusiness-friendlyDeveloper-friendlyGitHub traction
Launch readiness
8.2 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic open-sourced the Model Context Protocol, a standard for connecting AI assistants to external data sources and tools, with public repositories, SDKs, and reference…

AI Browser Agents

Computer use, upgraded Claude 3.5 Sonnet, and Claude 3.5 Haiku

Anthropic introduced computer use in public beta alongside an upgraded Claude 3.5 Sonnet and the new Claude 3.5 Haiku model.

Recheck due Free: No API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.8 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic introduced computer use in public beta — Claude operating graphical interfaces and desktop-style tasks — alongside an upgraded Claude 3.5 Sonnet and the…

AI Productivity Tools

Collaborate with Claude on Projects

Anthropic launched Projects in Claude.ai, letting Pro and Team users organize chats and knowledge into persistent workspaces.

Recheck due Free: No API: No Open: No
Clear use caseBeginner-friendlyBusiness-friendlyTraction signal
Launch readiness
6.6 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic launched Projects in Claude, letting Pro and Team users organize chats, uploaded knowledge, and instructions into persistent workspaces (anthropic.com). Enterprises, Researchers, and Operators…

AI Productivity Tools

Claude 3.5 Sonnet

Anthropic launched Claude 3.5 Sonnet, the first release in the Claude 3.5 model family, with strong intelligence, coding, vision, and API availability.

Recheck due Free: Yes API: Yes Open: No
Clear use caseBusiness-friendlyDeveloper-friendlyTraction signal
Launch readiness
7.2 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-08.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

Anthropic launched Claude 3.5 Sonnet, the first model in that family, with strong intelligence, coding, and vision available on free Claude access, Pro and…

How To Evaluate This Company

A useful Anthropic review should combine company-level context with product-level evidence. Start with the official site, then inspect the linked tools and launch records for source quality, pricing clarity, demo availability, audience fit, and how recently the profile was verified.

  • Check whether the company has a clear official product path, documentation, demo, pricing page, or public launch announcement.
  • Compare the linked tool profiles against the launch timeline to see whether the product story is current or stale.
  • Use the category and audience tags as discovery aids, then verify claims through the source links before making a buying, writing, or creator-coverage decision.
  • Treat unknown funding, founder, or contact fields as research gaps, not negative signals. They identify where the profile needs more public evidence.
  • When a launch or tool looks important but under-documented, submit a correction or related launch so the graph can be improved.

Editorial And Creator Coverage Notes

For Kingy AI, Anthropic is most interesting when the company has a clear product change, a useful demo surface, a founder or team story, a strong comparison angle, or a launch that helps buyers understand where the AI market is moving. The current graph gives editors and creators a starting point without pretending that every profile is already complete.

Good coverage candidates usually have a specific workflow, visible product proof, a concrete audience, and enough official or high-quality public sources to avoid thin summaries. If those pieces are missing, this page should be read as a research queue as much as a company profile.

Verification And Source Notes

The verification panel below summarizes profile freshness and key source checks. It is intentionally visible because AI company pages become low-trust quickly when dates, product claims, funding notes, or source links are not kept current.

Verification & Sources

Evidence state
Unknown
Source links
2
Freshness
Needs recheck: checked June 24, 2026
Last updated
June 8, 2026
What this evidence state means
Definition
Evidence is missing, insufficient, or conflicting, so Kingy is not asserting the claim as verified.
Required provenance
No qualifying evidence yet, or the available sources conflict. Any visible source links are context, not verification.
Owner
Kingy editorial triage owner
Freshness rule
No freshness claim. Review when qualifying evidence arrives and before the record becomes indexable as a complete profile.
Disputes and corrections
Use “Suggest a correction” on the record. Kingy editorial reviews the cited evidence, records material corrections, and changes or removes the state when it is not supported.

Key source checks

Suggest a correction

Form submissions, correction notes, score details, URLs, and analytics events may be stored for editorial review, spam prevention, product improvement, and follow-up. Do not submit secrets, unreleased financials, private customer data, or regulated personal data through these forms.