Client libraries, framework adapters and plugins that expose Jev inside an existing stack.
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TradingAgents combines fundamental, sentiment, news and technical analysts with debating researchers, a trader and risk management roles. With TYPESAFE_API_KEY, Jev removes unrelated StockTwits and Reddit posts and classifies stance; without the key, posts pass through unscreened.
AgentScope builds agents around model reasoning and tool use, with context management, event streaming, memory and permission controls. JevClassifierModel integrates the Jev classifier through the TypeSafe SDK within this broader agent framework.
Developers define allowed components and actions so generated interfaces follow their own catalog and schema. The playground's experimental composer uses typesafe-ai/jev to evaluate candidate components while building a UI specification.
This self-hosted trading stack covers Python strategies, backtests, paper trading, live execution and monitoring. Jev evaluates order, strategy, exposure, position and budget context, returning typed choices with probabilities for the entry filter.
Kev provides pretrained decision models and fine-tuning for yes/no, multiple-choice and rating questions over shared text. Its API follows TypeSafe System One, allowing the TypeSafe Python SDK to target a local Kev server.
This npm library and Claude Code plugin compact history by pruning tool calls and results instead of rewriting conversation text. Jev answers separate noul questions about retaining each call and result; thresholds determine whether to keep, shorten or remove the pair.
Instructions, tools, skills, channels and schedules live in conventional directories, making an agent project inspectable and extensible. The evaluate helper sends typed questions about supplied state through eve's model authentication, defaulting to Jev.
The native CLI supports an interactive shell, scripted requests and embedding, with skills, MCP servers and subagents. Jev receives review policy, context and the pending action, returning a clear or caution decision for the permission pipeline.
PyGPT is a multi-provider desktop assistant for Linux, Windows and macOS, with chat, agents, RAG and tool integrations. The Jev plugin exposes jev_evaluate(state, questions), returning Choice, Score or Noul results to the current model.
OpenInference supplies conventions and instrumentation for tracing AI applications, including model calls, retrieval and external tools. Its TypeSafe integration records systemOne calls as spans with JSON inputs and outputs, model and token usage; examples cover Choice, Noul and Score.
ollaya downloads named open decision models and serves typed questions through a local daemon. It implements TypeSafe-compatible endpoints for existing Jev clients, while remaining an independent project. Use its CLI, desktop app or MCP server; Modelfiles can package reusable question sets.
LocalJev translates typed decision requests into DiffusionGemma classification prompts and validates the generated probability output. Its Bun service exposes Jev’s response format through a standard OpenAI-compatible chat backend. Run it with Bun and an oMLX server, then direct TypeSafe SDK clients to the local API.
hippo-memory stores agent memories in SQLite, tracks provenance and lets feedback suppress incorrect memories. Its optional Jev reranker orders recalled memories and is disabled by default. Agents can remember and recall through the CLI or MCP, sharing memory across coding tools.
DSCODE is a macOS coding agent whose terminal interface, CLI and scripts share a persistent session runtime. The repository includes a separate Jev client for OpenRouter’s alpha Decisions endpoint, supporting Choice, Score and Noul. Use sessions for editing, tests and agent handoffs; the Jev client requires an API key.
The English and Simplified Chinese list collects Jev applications, clients, agent tools, games and research links. Start from the official documentation and known-failures links, then use the SDK or application sections to find an implementation.
phi is a Go terminal coding harness with file tools, subagents, diff review and on-demand MCP tool discovery. Configure a primary coding model with phi config, start phi, and supply TYPESAFE_API_KEY if enabling optimizer features.
Jev MCP gives agents tools for evidence verification, classification, reranking, extraction and patch review. Register npx -y @jkudish/jev-mcp in an MCP client using Node.js 22 or newer and a configured Jev provider key.
classifier.dev exposes HTTP and CLI text classification, including batches and multiple label dimensions. Pass labels and text in a URL, install the classify CLI, or POST items and dimensions to /v1/classify.
Web Search Plus adds web search and page extraction tools to Hermes, with routing and fallback across configured providers. Install the Hermes plugin and configure a search provider. Enable Jev separately with setup --jev and install typesafe-sdk.
System One Adapter implements the typesafe_sdk evaluation interface using other providers’ LLM APIs. It enables comparisons with TypeSafe while preserving typed answers and adding retry, latency and normalization diagnostics. Configure a provider, model and probability or discrete answer mode; native structured outputs are optional.
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.
Jev Browser runs a task from a starting URL and returns the final page, screenshot and decision trace. Use the npm CLI, MCP server or navigate library with Node.js 22 and a Jev provider key.
The plugin uses Jev to recommend available tools, skills and task owners and to evaluate output against defined criteria. Install the native DSH bundle or import the iPolloWork package, configure a TypeSafe key, then check status before a live connection test.
fingers combines several web fingerprint databases and can use Jev to review rule matches, deduplicate findings and refine versions. Install the Go library and enable the judge with EnableJudge and a TypeSafe key, or use the CLI’s jev-key option.