# Cursor, Grok, and agent skills + Jev

> Add jev-mcp to Cursor MCP config, install typesafe-ai/skills for Cloud Agents, and use Jev beside Grok or other models without custom Grok Bot APIs.

MCP in Cursor settings, TypeSafe skills in the agent, no imaginary Grok-only APIs.

## Answer

Cursor agents and Grok-powered bots still need gates: which skill to load, whether a command is safe, whether to escalate. Jev does that with probabilities; the editor's model does the talking.

## What Cursor provides

Cursor is an AI-native editor with chat, Cloud Agents, MCP server configuration, and agent skills (SKILL.md) loaded for compatible agent modes. There is no separate documented Grok Bot API for Jev: when you use Grok as a model inside Cursor or related X integrations, wire Jev the same way you would for any other model (MCP tools and skills).

## Register Jev MCP in Cursor

Community MCP servers document a Cursor mcpServers block. blakestone-x/jev-mcp is a common starting point (classify, score, check via uvx). Set TYPESAFE_API_KEY in the env block or your shell.

```json
{
  "mcpServers": {
    "jev": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/blakestone-x/jev-mcp@v0.2.1", "jev-mcp"],
      "env": { "TYPESAFE_API_KEY": "..." }
    }
  }
}
```

## Agent skills in Cursor

Install TypeSafe's official skill so the agent learns System One patterns before calling tools:

```bash
npx skills add typesafe-ai/skills --skill typesafe-ai
# Optional judge playbook:
npx skills add gecm0/jev-judge-mcp --skill jev
```

## jevwire and other MCP toolkits

Brainwires/jevwire documents multiple tools (jev_evaluate, jev_rank, jev_verify, jev_gate_action) and npm package jevwire for Streamable MCP. rashedInt32/jev-mcp and burnigtm/jev-mcp are alternate servers listed in the directory; compare tool surfaces before picking one.

## Grok in the loop

Demos such as pixelml-av-grok-jev show Grok generating answers while Jev filters evidence and checks support. That pattern is application-level (RAG plus refiner), not a Cursor-built Grok feature. In Cursor, you might use Grok as the chat model while Jev MCP tools handle decide steps; keep responsibilities split.

## Cloud Agents and keys

Cloud Agents need secrets in the environment the remote worker uses, not only your laptop shell. Follow Cursor documentation for MCP and env injection on cloud runs. Rotate keys if they ever appear in committed mcp.json.

## Environment keys

Create a key at https://console.typesafe.ai/ (or route through Vercel AI Gateway / OpenRouter where the integration documents it). Export TYPESAFE_API_KEY in the environment for Cursor MCP and agent processes. Some MCP clients accept AI_GATEWAY_API_KEY when using gateway-hosted Jev models; follow that integration's README. Never commit keys into repos or paste them into chat logs.

```bash
export TYPESAFE_API_KEY="tsk_..."
# Optional pin:
export TYPESAFE_MODEL="jev-latest"
```

## Pitfalls

Pin MCP package versions (git tags or npm versions) so builds do not drift. MCP tools are not automatic: the model must call them unless you use a separate hook-based plugin on Claude Code. Avoid stuffing every Jev MCP schema into context when you only need judge; pick one server. Read each server's license and data handling before sending production content.

## In the directory

- [All agent guides](https://jev.aitools.fyi/guides/jev-with-ai-agents)
- [System One primer](https://jev.aitools.fyi/learn/system-one)
- [Agent tooling](https://jev.aitools.fyi/categories/agent-tooling)
- [jev-mcp (blakestone-x)](https://jev.aitools.fyi/tools/blakestone-x-jev-mcp)
- [jevwire](https://jev.aitools.fyi/tools/brainwires-jevwire)
- [jev-mcp (rashedInt32)](https://jev.aitools.fyi/tools/rashedint32-jev-mcp)
- [TypeSafe agent skills](https://jev.aitools.fyi/sdks/typesafe-ai-skills)
- [Jev Ultrafast](https://jev.aitools.fyi/apps/browser-use-jev-ultrafast)

## FAQ

### Is there a Grok Bot-only Jev SDK?

We did not find one. Use standard TypeSafe credentials and documented MCP or HTTP APIs regardless of which chat model Cursor selects.

### Cursor vs Claude Code for jev-judge?

jev-judge-mcp targets Claude Code, Codex, and OpenCode explicitly. Cursor users typically register the same stdio server manually in MCP settings.

### Which jev-mcp fork?

blakestone-x/jev-mcp documents Cursor config. arunav25 and rashedInt32 forks add benchmarking or extra tools; read README diffs on the catalog detail pages.

### Skills vs MCP in Cursor?

Skills steer prompting and workflow design. MCP executes typed calls. Use both when the agent needs to know when to judge and a tool to do it.

### Gateway instead of direct TypeSafe?

See /learn/vercel-ai-gateway for AI_GATEWAY_API_KEY and model ids when your stack already routes through Vercel.

## Sources

Directory copy checked 2026-09-26. Primary sources:

- [blakestone-x/jev-mcp README](https://github.com/blakestone-x/jev-mcp?ref=jev.aitools.fyi)
- [typesafe-ai/skills](https://github.com/typesafe-ai/skills?ref=jev.aitools.fyi)
- [jev-judge-mcp README](https://github.com/gecm0/jev-judge-mcp?ref=jev.aitools.fyi)
- [Cursor MCP docs](https://docs.cursor.com/context/mcp?ref=jev.aitools.fyi)
- [TypeSafe System One docs](https://docs.typesafe.ai/concepts/system-one?ref=jev.aitools.fyi)

Canonical: https://jev.aitools.fyi/guides/jev-with-ai-agents/cursor-mcp-and-skills
Markdown: https://jev.aitools.fyi/guides/jev-with-ai-agents/cursor-mcp-and-skills.md