AI Law Tracker

Get upcoming AI-law deadlines

get_ai_deadlines

Read-onlyIdempotent

The upcoming AI-law effective / compliance-date calendar, derived deterministically from the curated corpus (no LLM). Each entry carries the verbatim source deadline text + primary-source URL; jurisdictions whose deadline text has no explicit date are reported only as meta.undated (never given an invented date). Free at every tier. This tool returns JSON; a compliance team can also SUBSCRIBE to the same feed as a live RFC 5545 calendar at https://ai-law-tracker.com/api/v1/deadlines?format=ical (webcal). NOT legal advice.

Input Schema

TableJSON Schema

Name	Required	Description
`all`	No	Alias to include past dates as well (equivalent to upcoming=false).
`scope`	No	One of: state, federal, eu, global.
`upcoming`	No	Only future dates (default true). Set false to include past effective dates too.
`jurisdiction`	No	Exact jurisdiction slug (e.g. california, us-federal, eu, canada). See list_jurisdictions.

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context: deadlines are derived deterministically, no LLM, no invented dates, and undated entries are not given invented dates. This goes beyond annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is informative but slightly verbose. It front-loads the key purpose and adds useful details like determinism and no legal advice. Could be trimmed slightly, but still efficient for the information provided.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description provides sufficient context: each entry has verbatim text and source URL, undated entries are meta.undated, and it notes the tool returns JSON. This is complete for a calendar tool with no required parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline 3. The description adds meaning by explaining the 'all' alias for past dates and referencing list_jurisdictions for the jurisdiction parameter. This provides helpful guidance beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns 'upcoming AI-law effective/compliance-date calendar' derived deterministically from a curated corpus. It specifies the tool returns JSON with verbatim deadline text and source URL, distinguishing it from siblings like list_ai_laws which list laws, not deadlines.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions it's free at every tier and provides an alternative subscription method (iCal feed). It notes undated entries are reported as meta.undated. However, it does not explicitly say when to use this tool vs siblings like get_ai_law or list_ai_laws, though context implies it's for deadlines specifically.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All AI Law Tracker tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0

Disambiguation1/5

Multiple tools are nearly interchangeable: assess_ai_compliance and generate_compliance_report both take a business profile and return risk score plus obligations, and get_sector_detail overlaps with get_ai_obligations/get_ai_penalties. Additionally, list_recent_changes and list_law_feed both describe dataset changes, while list_jurisdictions overlaps with list_countries and list_us_states. An agent cannot reliably pick the right tool without reading fine print.

Naming Consistency4/5

The set mostly follows a consistent snake_case verb_noun pattern (get_ai_law, list_sectors, search_court_opinions). Minor deviations exist: assess_ai_compliance and generate_compliance_report use different verb styles for near-identical actions, and list_ai_law_news is inconsistent with list_ai_laws. Overall the pattern is still predictable and readable.

Tool Count2/5

With 28 tools, the server exceeds the comfortable range and includes several redundant or overlapping endpoints that could be consolidated. The broad domain justifies a larger surface, but duplicates like assess_ai_compliance/generate_compliance_report and the three jurisdiction listers make the count feel inflated rather than well-scoped.

Completeness4/5

The tool surface covers the core read-only AI-law workflow well: search and retrieve laws, obligations, penalties, deadlines, sectors, jurisdictions, bills, court opinions, news, and change history. Minor gaps remain, such as no way to fetch a single obligation/penalty record by ID and no separate news-detail endpoint, but these are workable and not dead ends.

Resources

Need Help?