Local Markdown library of the papers an evidence review cites: metadata, abstract and full text
Its author marked it deprecated in the MCP Registry
AI exposure scores (0-100) for ~1,000 U.S. occupations, and recent AI-attributed layoffs.
AI-Safe Careers is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
AI exposure scores (0-100) for ~1,000 U.S. occupations, and recent AI-attributed layoffs.
# 1 — add it to Claude Code
claude mcp add --scope user --transport http ai-safe-careers-mcp https://aisafe.careers/mcp
# 2 — ask your agent for something these tools do
# get_ai_exposure, search_occupations, recent_ai_attributed_layoffs
AI-Safe Careers costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http ai-safe-careers-mcp https://aisafe.careers/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
3 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
What the model actually sees. Descriptions are diffed on every release — see version history.
Look up the AI Exposure Score (0-100) for a job title: its band (Low, Moderate, Elevated, High, Very High), percentile, example tasks that are automatable, augmentable or durable, and adjacent careers with their scores. Scores are precomputed estimates of how much of a role's tasks overlap with what AI can do, built from O*NET and published research; they are not predictions that a job will disapp
| Parameter | Type | Required | Notes |
|---|---|---|---|
| job_title | string | yes | A job title, for example "registered nurse" or "data analyst". |
Find occupations whose titles match a search, with each one's AI Exposure Score, band and page URL. Use it when a job title is ambiguous, then call get_ai_exposure with the exact occupation.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | yes | Words from a job title. |
| limit | integer | no | How many matches to return (default 8). |
Recent layoffs where the company itself cited AI as a reason, from AI-Safe Careers' curated tracker, each with its date, approximate headcount and source. All-cause layoffs (layoffs.fyi, WARN notices) are tracked separately and are never included here, so these are not a count of all job cuts.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| limit | integer | no | How many events to return (default 10). |
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install AI-Safe Careers or to call it, at any volume.
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | minimal | capability blast radius (minimal) — client exposure if the model is manipulated | −0 |
| coverage-honesty | manifest | inspection depth (manifest) — how much of the target the scan could see | −4 |
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
The scan read each tool’s name, description, input schema and annotations exactly as the server listed them the last time it answered us; no code was reviewed. We ask the server again about once a month, and a list that changed is graded again.
The implementation source was not read — this reflects the declared tool metadata only.
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. minimal is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| get_ai_exposure | no tags | |
| search_occupations | no tags | |
| recent_ai_attributed_layoffs | no tags |
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.0.0.
No release note was published with this version.
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Any signed-in account that does not publish AI-Safe Careers can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.