Discover the Best AI Tools

Self-hosted log ingestion, semantic search, question answering and anomaly dashboards built around ClickHouse and Qdrant. Uses Groq or local Ollama, with optional Jev query classification; generated explanations require checking against the logs.

TypeScript library and read-only MCP server for financial day counts, accrued interest, business days and payment schedules. Calendars use coded rules and pinned exceptional closures that require updates.

Native terminal multiplexer keeps sessions in a background server and optionally ranks palette commands with Jev. Local search works without a key; semantic ranking requires provider access, and Windows uses a WSL2 server.

Chrome side panel uses Jev to select and fill tools exposed by a page’s WebMCP schemas. Requires WebMCP support and a TypeSafe key; state-changing calls need confirmation, and array arguments currently populate only their first element.

LLM Debugger is a VS Code research extension that runs a program, sets breakpoints and inspects runtime values, using Jev for action choices and a text model for hypotheses and patches. It requires model credentials and actually executes target code. It is an unsupported proof of concept; small example benchmarks do not guarantee general debugging success.

Claude Code Trace displays and tails local Claude Code JSONL sessions in desktop, web or terminal interfaces. Optional Jev analysis highlights repeated work and efficiency patterns after previewing and confirming a redacted payload. Its scores are model judgments, not measured monetary cost; viewing is local, but optional analysis sends trace content externally.

Argentum provides MCP tools for agent reputation, attestations and signed action trails anchored on-chain. Trails omit original action inputs; reproducing an action therefore depends on the operator retaining them. Chain receipts document recorded claims and integrity, not automatic proof of correct behavior or regulatory compliance, and chain operations require infrastructure and fees.

CashPilot MCP exposes earnings, worker status and logs from an existing CashPilot instance, plus service deployment and lifecycle controls. It needs that instance's admin API key and supports HTTP or stdio. Remote exposure requires deliberate authentication configuration; this bridge neither creates passive income nor guarantees returns.

M-Pesa MCP connects agents to Safaricom Daraja payment prompts and status queries, plus Africa's Talking SMS and airtime. It requires provider credentials and callback configuration, with sandbox and production modes. Production actions can transfer value or send messages; documented validation and logging are not independent security certification.

Indexes local folders for lexical, vector and hybrid search through MCP. Default vectors use lexical feature hashing rather than neural embeddings; neural models and Jev reranking are optional additions.

Reranks Google organic search results using Jev and configurable rules, with restoration of the original order. Uses result titles, URLs and snippets rather than full pages; currently supports www.google.com and requires a paid API key.

A Node MCP browser server using Playwright and Jev to jointly choose actions, elements and supplied literal text. Requires Chromium and model access; callers provide text values, and probabilistic decisions are not a security boundary.

Proxies Playwright MCP with Jev-based page triage, content pruning and risk checks. Without an API key it passes requests through; model judgments are not a security guarantee or authorization mechanism.

A Python local web UI for browser automation: Jev selects bounded actions while a separate text model supplies field values. Supports manual and automatic steps with traces; requires model credentials.

Provides browser task benchmarks and a bounded Jev automation loop over Chrome CDP. Requires browser and API setup; benchmark timing excludes planning and does not establish general performance.

Connects coding agents to Dodo payment operations and searchable documentation through remote MCP servers. Payment actions require OAuth and can change real accounts.

Python automation layer separates code-owned observation, execution and verification from a model’s single bounded action choice. Requires configured browser or desktop adapters and provider access; caller-written checks determine whether a task really succeeded.

Minimal runnable reference skill lets Jev select bounded browser operations from observed controls. Requires browser setup and model credentials; it targets ordinary pages and omits the fuller inspection and guard features of the upstream implementation.

CLI and MCP browser layer lets Jev choose Chrome actions while a calling agent supplies goals and literal text. Requires a compatible model provider and browser; benchmarks cover limited tasks and uncertain runs return control for review.

Typed SDK, persistent CLI and MCP combine native Playwright actions with Jev semantic selection and assertions. Native operations need no model key; semantic features require a decision backend, and inconclusive model evidence should not be treated as success.

Runnable spectator demo compares two Jev agents playing Snake through indexed browser controls. Real model play requires a TypeSafe key; without one it clearly uses deterministic rules. This narrow demonstration is not a general agent benchmark.

Jev Frontend QA runs contract-based or exploratory browser checks with Jev, Browser Harness and optional host-planned subgoals. It correlates DOM, HTTP and persistence evidence into reports; exploration is not a contract pass. It needs Chrome and live TypeSafe access, while native selects, embedded contexts and popup workflows remain unsupported.

Jev Mobile persists Android tasks in SQLite and runs a single worker that observes, decides, journals, mutates and verifies a USB-connected device. It needs Android/ADB access and TypeSafe credentials. Validated scope focuses on notes, checklists and recovery; sensitive actions and unknown permission dialogs escalate rather than run autonomously.

PlayJev extends an existing Playwright page with natural-language actions, form filling and state checks driven by Jev. It keeps the underlying Playwright API and chooses from observed controls. Chromium/CDP and a TypeSafe key are required. The API is experimental; small live smoke tests do not establish broad browser reliability.