System One Connector exposes typed decisions to coding agents through its evaluate command and MCP integration. It connects to Jev or compatible self-hosted models such as CLM and Laya. Define Choice, Noul or Score questions; agent setup and batch evaluation are provided.
Agent Tooling for Jev — page 2
1206 repositories with documented relationships and source evidence.
Define semantic expectations in perch.yaml, scoped to files or methods, and inspect the resulting code findings. The System One client asks typed questions about supplied state, defaults to jev-latest and calls TypeSafe's API.
Jev Codex Router chooses model capability and thinking effort for each Codex model call, including tool continuations. Use the documented macOS setup with Codex desktop, Node.js, Python and a TypeSafe key, then install the embedded stack and select its router.
JevRouter selects among models, agents, skills, MCP tools and CLIs, exposing single decisions or multistep capability plans. Use the route or plan CLI, SDK or agent setup with TypeSafe or OpenRouter credentials; a labeled demo provider works offline.
jev-gateway routes tool decisions for coding agents through Jev while the usual language model handles other work. Install the npm package and start an existing authenticated agent with its jev- launcher, then configure the Jev provider once.
Self-hosted, versioned skills library for AI agents. MCP, scoped clients, and optional Jev recommendations.
Email inbox API for AI agents. Give every agent its own real email address, receive mail as structured webhooks, and reply in-thread over REST. A complete multi-tenant mail server in Rust: inbound and outbound, DKIM/SPF/DMARC/ARC, MTA-STS, DANE, three-tier anti-spam.
Local-first MCP plugin for continuous software-quality review by AI coding agents, powered by Jev.
Fastest measured Qwen3.8-27B config for DGX Spark (GB10): SGLang + NVFP4 + DFlash2, 72 tok/s greedy median, 1M context, deterministic boots. Flash-Next 176B on one box. One command, everything pinned, and a local cockpit to drive it.
Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs DeepSeek, Qwen, Doubao, Claude or Ollama (BYOK), MCP, and can drive Claude Code / Codex CLI. 开源 AI 办公助理,豆包办公 / 千问办公替代。
The System One harness for System One models. Run Jev and other System One models locally or directly on HarnessRouter.ai.
Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it
Guardrails for Pi that steer instead of interrupt: enforces your project rules on every write, holds only hard-to-undo actions (3 per 1,000 calls, measured on real sessions), catches unverified "done" claims and stuck loops, and trims tool output. Built on pi-typesafe.
TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers
API server runtime for common AI use cases — supports multiple models and providers. Run locally with Ollama or LM Studio, or in the cloud via OpenRouter, OpenAI, Anthropic, or Google.
The pipe layer of an AI nervous system — one interface connecting provider neurons to your application, across three inference types: generate, stream, and a calibrated decide (via TypeSafe Jev). MCP-native, voice (TTS/STT/realtime), RAG, memory, file processors. Powers Tara, Yama and Clairvoyance at Juspay.
A skill for writing and improving programs that call Jev, TypeSafe's System One model
Coverage, security and code quality for coding agents
RAGElo is a set of tools that helps you selecting the best RAG-based LLM agents by using an Elo ranker
《Jev 工程学:为 coding agent 而作》完整中文翻译 — 保留原结构与 7 张插图
The ai agent workflow tool that scales from small, simple projects to large, complex codebases.
Rust CLI powered by Jev from TypeSafe.ai that ranks agent skills for the next step using live session context. Includes Claude Code hooks, structured JSON, abstention, and local feedback. Requires a TypeSafe API key.
This is the repository for the LatteReview python package. LatteReview is a low-code Python package designed to automate systematic literature review processes through AI-powered agents.
A small extension that demos the combination of Jev x WebMCP