AI company impact profile

Anthropic

Maker of Claude, with growing enterprise and developer-tool distribution.

Current measured public footprint68

Rank #2 · Large observable footprint

Stable attention

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Data effective Jul 18, 2026, 12:00 AM UTC · recomputed Jul 19, 2026, 6:30 AM UTC

How to read 68

A footprint measurement, not a verdict

The score normalizes public attention, official developer activity, evidence-backed gains, evidence-backed problems, and source breadth across the measured company set.

It does not mean: that Anthropic is the “best,” safest, most valuable, or most responsible company. Documented problems contribute to visible footprint rather than being hidden as a negative subtraction.

Read the complete methodology →

Methodology version: visible-impact-v1
Evidence confidence: Moderate
Accountability risk: Moderate
7-day movement: Not enough history
30-day movement: Not enough history

Normalized components

What is inside the score

30% weight100

Public attention

30-day English Wikipedia pageviews, normalized across the measured set

100

25% weight80

Developer ecosystem

stars and public repositories in the company’s official GitHub organization

20% weight26

Evidence-backed gains

independent stored sources attached to company-linked gain readings

20% weight56

Evidence-backed problems

independent stored sources attached to company-linked problem readings

5% weight40

Evidence breadth

unique independent sources in the published Truvace record

Observed history

Measured-impact score over all available time

Fixed 0–100 scale

Anthropic · circle

Lines connect observed snapshots only. Gaps do not mean a score stayed unchanged. Diamond markers indicate a methodology-version transition.

View the history as a data table

Persisted measured-impact scores and methodology versions
Effective date	Anthropic
Jul 18, 2026	69 · visible-impact-v1

No interpolation

Score, rank, gain, and problem history

Most recent persisted score snapshots for Anthropic
Effective	Score	Rank	Gain	Problem	Method
Jul 18, 2026, 12:00 AM UTC	69 (+1)	#2 (0)	26	56	visible-impact-v1
Jul 18, 2026, 12:00 AM UTC	68	#2	26	56	visible-impact-v1

Evidence profile

Coverage and gaps

Associated records: 3
Gain claims: 1
Problem claims: 2
High-evidence claims: 0
Independent sources: 2
Date range represented: 2026-07-18 to 2026-07-18

Sector distribution

Crime2
Labor1

Known evidence gap

Private usage volumes, customer concentration, and revenue composition are not disclosed.

Linked to the record

Associated gain and problem evidence

Claims are sorted by their existing Sourced Index impact score. Each card links to its Truvace record and original sources; company marketing is not treated as independent proof.

Anthropic

1 gain · 2 problem · 0 high-evidence

problemCrimeModerate evidenceImpact 83
7.2% of evaluated MCP servers contained general vulnerabilities and 5.5% exhibited MCP-specific tool poisoning, part of eight distinct vulnerabilities largely distinct from traditional software flaws.
In a first large-scale empirical study published May 2026, researchers examined 1,899 open-source Model Context Protocol servers, the standard introduced by Anthropic in late 2024 to unify tool calling for Foundation Models. Using health metrics and a combined general and MCP-specific scanner, they measured adoption signals and code quality across the ecosystem.
Jul 13, 2026
1 source
- ACM Transactions on Software Engineering and MethodologyPeer-reviewed
gainCrimeModerate evidenceImpact 78
Open-source MCP servers demonstrated strong health metrics despite rapid adoption with SDK downloads surpassing twenty five million per week.
In a first large-scale empirical study published May 2026, researchers examined 1,899 open-source Model Context Protocol servers, the standard introduced by Anthropic in late 2024 to unify tool calling for Foundation Models. Using health metrics and a combined general and MCP-specific scanner, they measured adoption signals and code quality across the ecosystem.
Jul 13, 2026
1 source
- ACM Transactions on Software Engineering and MethodologyPeer-reviewed
problemLaborModerate evidenceImpact 66
Software workers face job loss as AI coding tools transform the industry, with Atlassian laying off 10% of staff
Australian software company Atlassian announced it will lay off 10% of staff, bringing the AI and jobs debate into focus. The article notes the software industry has been transformed, with developers reporting productivity changes from Anthropic's AI-powered coding tool Claude.
Jul 12, 2026
1 source
- The GuardianJournalism

Recorded changes

Evidence events

Jul 12, 2026, 8:54 PM UTCproblem claimemerging evidence · impact 66Open claim
Jul 13, 2026, 8:35 AM UTCgain claimmoderate evidence · impact 78Open claim
Jul 13, 2026, 8:35 AM UTCproblem claimmoderate evidence · impact 83Open claim

AI company impact profile

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Loading company impact history and evidence.

A footprint measurement, not a verdict

The score normalizes public attention, official developer activity, evidence-backed gains, evidence-backed problems, and source breadth across the measured company set.

Read the complete methodology →

Persisted measured-impact scores and methodology versions

Effective date

Anthropic

Jul 18, 2026

69 · visible-impact-v1

Most recent persisted score snapshots for Anthropic

Effective

Score

Rank

Gain

Problem

Method

Jul 18, 2026, 12:00 AM UTC

69 (+1)

#2 (0)

visible-impact-v1

Jul 18, 2026, 12:00 AM UTC

visible-impact-v1

Anthropic

1 gain · 2 problem · 0 high-evidence

problemCrimeModerate evidenceImpact 83
7.2% of evaluated MCP servers contained general vulnerabilities and 5.5% exhibited MCP-specific tool poisoning, part of eight distinct vulnerabilities largely distinct from traditional software flaws.
In a first large-scale empirical study published May 2026, researchers examined 1,899 open-source Model Context Protocol servers, the standard introduced by Anthropic in late 2024 to unify tool calling for Foundation Models. Using health metrics and a combined general and MCP-specific scanner, they measured adoption signals and code quality across the ecosystem.
Jul 13, 2026
1 source
- ACM Transactions on Software Engineering and MethodologyPeer-reviewed
gainCrimeModerate evidenceImpact 78
Open-source MCP servers demonstrated strong health metrics despite rapid adoption with SDK downloads surpassing twenty five million per week.
In a first large-scale empirical study published May 2026, researchers examined 1,899 open-source Model Context Protocol servers, the standard introduced by Anthropic in late 2024 to unify tool calling for Foundation Models. Using health metrics and a combined general and MCP-specific scanner, they measured adoption signals and code quality across the ecosystem.
Jul 13, 2026
1 source
- ACM Transactions on Software Engineering and MethodologyPeer-reviewed
problemLaborModerate evidenceImpact 66
Software workers face job loss as AI coding tools transform the industry, with Atlassian laying off 10% of staff
Australian software company Atlassian announced it will lay off 10% of staff, bringing the AI and jobs debate into focus. The article notes the software industry has been transformed, with developers reporting productivity changes from Anthropic's AI-powered coding tool Claude.
Jul 12, 2026
1 source
- The GuardianJournalism

A footprint measurement, not a verdict

What is inside the score

Public attention

Developer ecosystem

Evidence-backed gains

Evidence-backed problems

Evidence breadth

Measured-impact score over all available time

Score, rank, gain, and problem history

Coverage and gaps

Sector distribution

Known evidence gap

Associated gain and problem evidence

Anthropic

7.2% of evaluated MCP servers contained general vulnerabilities and 5.5% exhibited MCP-specific tool poisoning, part of eight distinct vulnerabilities largely distinct from traditional software flaws.

Open-source MCP servers demonstrated strong health metrics despite rapid adoption with SDK downloads surpassing twenty five million per week.

Software workers face job loss as AI coding tools transform the industry, with Atlassian laying off 10% of staff

Evidence events

Loading company evidence…

A footprint measurement, not a verdict

What is inside the score

Public attention

Developer ecosystem

Evidence-backed gains

Evidence-backed problems

Evidence breadth

Measured-impact score over all available time

Score, rank, gain, and problem history

Coverage and gaps

Sector distribution

Known evidence gap

Associated gain and problem evidence

Anthropic

7.2% of evaluated MCP servers contained general vulnerabilities and 5.5% exhibited MCP-specific tool poisoning, part of eight distinct vulnerabilities largely distinct from traditional software flaws.

Open-source MCP servers demonstrated strong health metrics despite rapid adoption with SDK downloads surpassing twenty five million per week.

Software workers face job loss as AI coding tools transform the industry, with Atlassian laying off 10% of staff

Evidence events