# Akil

**Canonical:** https://apis.io/providers/askakil-ai/  
**Website:** https://askakil.ai/  
**APIs profiled:** 0

Akil provides AI‑ready access to New York City public records, offering a curated toolkit of over 200 data sources such as building permits, school information, and city council actions. By connecting these datasets to AI assistants, Akil enables developers to build intelligent applications that query, explain, and visualize municipal data with source attribution and coverage limits.

## Kin Score — 8.1 / 100 (minimal)

Scored 2026-11-06 under rubric 0.27.0. Trend: flat (-3.6 from 11.7).

| Facet | Score |
|---|---|
| Discoverability | 48.3 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 4.8 |
| Access Clarity | 10.5 |

Regulatory layer — **Government & Public Sector**: 14.5 (matched via tags).

## Agent readiness — 22.2 (agent-aware)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | documented |
| Auth Clarity | served |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | served |
| Protected Resource Metadata | verified |
| Dynamic Client Registration | yes |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |
| MCP Tool Quality | na |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## MCP servers (1)

- **Akil MCP Server** — Remote MCP server at mcp.askakil.ai requiring an API key.

## Security (1)

- **Askakil Ai Domain Security** — TLSv1.3

## Tags

Data, NYC, Public Records, Artificial Intelligence, Government

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/askakil-ai/). Scores are computed from the provider's own public artifacts under a published rubric.