compare_cohorts
Education vs Government: public-sector APIs trail the classroom
EdTech outscores government and public-sector providers by 3.8 points. The largest gap is access clarity.
Education & EdTech
Government & Public Sector
Each sun is drawn from the cohort's averages: six facet rings, the mean Kin Score and mean agent readiness.
Both sectors publish APIs because they have to: schools for rostering and learning tools, governments for open data and digital services. The 1,035 scored education and EdTech providers average 21.2, against 17.4 for 891 government and public-sector providers. The medians are further apart, 18.4 against 11.2.
The widest gap is access clarity, 24.7 against 14.0. EdTech companies sell their APIs and say how to get in. Government APIs are often free but undocumented on how to obtain access. Education also leads on OAuth scopes (14% against 5%), which suits the student-data consent rules the sector works under. Contract quality (16.7 against 13.7) and developer ergonomics (19.7 against 17.6) follow.
Government has the higher ceiling (71.6 against 69.3) and is level on discoverability (58.8 against 58.5). Public data is easy to find and harder to use. The delta is depth-confounded by two artifact directories on the median member.
The distributions
| Education & EdTech | Government & Public Sector | Delta | |
|---|---|---|---|
| Kin Score, mean | 21.2 | 17.4 | +3.8 |
| Kin Score, median | 18.4 | 11.2 | +7.2 |
| Kin Score, highest | 69.3 | 71.6 | |
| Kin Score, std dev | 13.8 | 13.7 | |
| Agent readiness, mean | 10.4 | 8.8 | +1.6 |
| Agent readiness, highest | 61.6 | 67 |
Delta is Education & EdTech minus Government & Public Sector, as the tool returns it.
Where the providers sit
Education & EdTech
Government & Public Sector
Facet averages
| Facet | Education & EdTech | Government & Public Sector | Delta |
|---|---|---|---|
| Discoverability | 58.5 | 58.8 | -0.3 |
| Contract Quality | 16.7 | 13.7 | +3 |
| Contract Governance | 6.4 | 5.3 | +1.1 |
| Operational Transparency | 11 | 9.4 | +1.6 |
| Developer Ergonomics | 19.7 | 17.6 | +2.1 |
| Access Clarity | 24.7 | 14 | +10.7 |
What they publish
Share of each cohort's providers publishing each artifact. mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
| Artifact | Education & EdTech | Government & Public Sector | Delta |
|---|---|---|---|
| First-party MCP server | 5% | 5% | 0 |
| Any MCP artifact (incl. derived) | 6% | 5% | +1 |
| OAuth scopes | 14% | 5% | +9 |
| Spectral rules | 20% | 14% | +6 |
| Arazzo workflows | 1% | 1% | 0 |
| Agent skills | 0% | 0% | 0 |
| Security artifact | 99% | 99% | 0 |
How well we know each cohort
The coverage behind the averages. A cohort with a higher catalog gap and fewer artifact directories has been enriched less, so part of any difference is our coverage rather than the market.
| Education & EdTech | Government & Public Sector | |
|---|---|---|
| Declared members | 1101 | 913 |
| Scored (in the averages) | 1035 (94%) | 891 (98%) |
| Thinly covered | 928 | 834 |
| Median artifact directories | 9 | 7 |
| Mean catalog gap (points we could add) | 76.3 | 78.2 |
The full compare_cohorts response
{"a":{"kind":"industry","slug":"education","name":"Education & EdTech","members":1101,"stats":{"kind":"industry","slug":"education","name":"Education & EdTech","tier":"report","coverage":{"declared_members":1101,"resolved_members":1101,"scored_members":1035,"agent_scored_members":1035,"scored_share_pct":94,"unexamined_members":64,"enrichment_depth":{"mean_catalog_gap":76.3,"median_artifact_dirs":9,"n":1035,"thinly_covered":928,"thinly_covered_of":1035,"thin_coverage_note":"928 of 1035 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.","note":"Rubric points API Evangelist could add to the average member with no action by the providers, and the median count of artifact directories we hold on them. A cohort with a higher gap and thinner artifacts has been enriched less, so part of any difference between its mean and another cohort's is our coverage rather than the market. Compare two cohorts only when this figure is comparable. It is an upper bound on our backlog: it says who CAN close a gap, not who did."},"unexamined_note":"Excluded from the distribution: these carry a catalog-owned needs_work flag (never enriched, or no resolvable host). They are listed as members and keep their own page and score; they do not vote in the averages, because their score measures our coverage rather than their posture."},"sufficient":true,"kin_score":{"mean":21.2,"median":18.4,"min":0,"max":69.3,"stdev":13.8},"agent_readiness":{"mean":10.4,"median":2.5,"min":0,"max":61.6,"stdev":12.9},"band_distribution":{"exemplar":4,"strong":19,"developing":93,"thin":223,"emerging":415,"minimal":281},"facet_averages":{"discoverability":{"mean":58.5,"n":1035},"contract_quality":{"mean":16.7,"n":1035},"contract_governance":{"mean":6.4,"n":1035},"operational_transparency":{"mean":11,"n":1035},"developer_ergonomics":{"mean":19.7,"n":1035},"access_clarity":{"mean":24.7,"n":1035}},"adoption":{"mcp_pct":6,"mcp_first_party_pct":5,"mcp_note":"mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.","skills_pct":0,"scopes_pct":14,"security_pct":99,"arazzo_pct":1,"rules_pct":20}}},"b":{"kind":"industry","slug":"government","name":"Government & Public Sector","members":913,"stats":{"kind":"industry","slug":"government","name":"Government & Public Sector","tier":"report","coverage":{"declared_members":913,"resolved_members":913,"scored_members":891,"agent_scored_members":891,"scored_share_pct":98,"unexamined_members":21,"enrichment_depth":{"mean_catalog_gap":78.2,"median_artifact_dirs":7,"n":891,"thinly_covered":834,"thinly_covered_of":891,"thin_coverage_note":"834 of 891 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.","note":"Rubric points API Evangelist could add to the average member with no action by the providers, and the median count of artifact directories we hold on them. A cohort with a higher gap and thinner artifacts has been enriched less, so part of any difference between its mean and another cohort's is our coverage rather than the market. Compare two cohorts only when this figure is comparable. It is an upper bound on our backlog: it says who CAN close a gap, not who did."},"unexamined_note":"Excluded from the distribution: these carry a catalog-owned needs_work flag (never enriched, or no resolvable host). They are listed as members and keep their own page and score; they do not vote in the averages, because their score measures our coverage rather than their posture."},"sufficient":true,"kin_score":{"mean":17.4,"median":11.2,"min":0,"max":71.6,"stdev":13.7},"agent_readiness":{"mean":8.8,"median":0.6,"min":0,"max":67,"stdev":13.2},"band_distribution":{"exemplar":3,"strong":16,"developing":59,"thin":136,"emerging":235,"minimal":442},"facet_averages":{"discoverability":{"mean":58.8,"n":891},"contract_quality":{"mean":13.7,"n":891},"contract_governance":{"mean":5.3,"n":891},"operational_transparency":{"mean":9.4,"n":891},"developer_ergonomics":{"mean":17.6,"n":891},"access_clarity":{"mean":14,"n":891}},"adoption":{"mcp_pct":5,"mcp_first_party_pct":5,"mcp_note":"mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.","skills_pct":0,"scopes_pct":5,"security_pct":99,"arazzo_pct":1,"rules_pct":14}}},"comparable":true,"delta":{"kin_score_mean":3.8,"kin_score_median":7.2,"agent_readiness_mean":1.6,"facets":{"discoverability":-0.3,"contract_quality":3,"contract_governance":1.1,"operational_transparency":1.6,"developer_ergonomics":2.1,"access_clarity":10.7},"adoption":{"mcp_pct":1,"mcp_first_party_pct":0,"mcp_note":null,"skills_pct":0,"scopes_pct":9,"security_pct":0,"arazzo_pct":0,"rules_pct":6},"enrichment_depth":{"mean_catalog_gap":-1.9,"median_artifact_dirs":2}},"depth_confounded":true,"depth_note":"Education & EdTech scores 3.8 points higher than Government & Public Sector AND is the better-enriched cohort: 1.9 points less catalog_gap and 2 more artifact directories on the median member. The market difference and our coverage difference point the same way, so this delta cannot be attributed to the markets on its own. Close the enrichment gap, or report both figures together."}
Result read 2026-10-27. Education & EdTech and Government & Public Sector each have their own page with the full roster and leaderboard.
Run this comparison yourself
Everything above came from one call to compare_cohorts. Swap in any two tags, industries, regions, areas or VC portfolios and you get the same answer for your own shortlist. It is an Understanding tool, included in the Understanding and Influence plans, or pay per call.
https://apis.io/mcp:
{"name": "compare_cohorts", "arguments": {"a": "industry:education", "b": "industry:government"}}
Over the REST API:
curl "https://apis.io/api/v1/cohorts/compare?a=industry:education&b=industry:government" \
-H "X-API-Key: $APIS_IO_KEY"
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