AI Agent2026
Scans AI agent skills for security issues—detecting vulnerabilities, malicious patterns, and supply-chain risks before installation. Combines static AST checks (64 patterns across 16 categories) with optional LLM semantic review, OSV live CVE lookups, and JSON/Markdown/SARIF outputs for CI or manual review.
AI Client2026
Provides a local browser workspace for browsing and managing pi coding agent sessions — real-time chat, model configuration, skill management, and project file preview. Runs from a single npx/global install, scopes file access to the selected project, and follows Git worktrees.
AI Agent2026
Provides a persistent, typed semantic memory layer for AI agents—supports remember, recall, and answer primitives so agents retain long-term context. Writes are instantly searchable and retrieval uses an information-theoretic engine, avoiding separate vector DBs or indexing delays.
MCP Client2026
Indexes a repository into a local, queryable index (graph, git, docs, decisions, code health) and exposes task-shaped MCP tools so coding agents and developers get cited answers, symbol-level blast radius, test impact, refactoring plans and dead-code detection; self-hosted (AGPL-3.0) and needs no API key for deterministic analysis.
AI Agent2026
A curated collection of Korea-focused AI agent skills that enable agents to perform local tasks — ticket booking, public-data lookups, e-commerce and messaging integrations — via prebuilt connectors and an optional hosted proxy for API keys and fallbacks.
AI Agent2026
Manages discovery, quality evaluation, sharing and evidence-driven evolution of skills used by AI agents. Local-first deployment with MCP integration, CLI and Python API, skill lineage and task-based quality summaries for auditable agent workflows.
AI Agent2026
Runs and monitors AI agents inside real terminal panes, surfacing agent state (blocked / working / done) and keeping agents persistent across detach/reattach. Offers workspaces, tabs, panes, socket-API integrations, and a single Rust binary for macOS/Linux.
MCP Server2026
Bridges an LLM assistant to your locally running TradingView Desktop via Chrome DevTools Protocol for AI-assisted chart analysis, Pine Script development, and UI automation. Key features: Claude Code MCP integration, a JSON/CLI 'tv' toolset, local-only operation and streamable chart data.
AI Client2026
Integrates Codex into Claude Code so you can run read-only code reviews, steerable adversarial reviews, and delegate long-running tasks to a local Codex instance via slash commands. Uses the local Codex CLI/app server and Node.js; designed for developers who want seamless handoff between Claude Code and Codex.
AI Agent2026
Runs an LLM-driven agent loop that iteratively proposes, applies, tests, and commits small repo changes—each successful iteration becomes a separate git commit while failures are rolled back or preserved for repair. Supports multiple agent backends, worktrees for concurrency, live terminal status, and optional per-iteration pushes.
AI Agent2026
Turns natural-language instructions into runnable trading research: data loaders, strategy generation, backtests, reports, and optional broker connectors. Focuses on a tool-driven agent model (36+ MCP tools, 77 finance skills) and an Alpha Zoo of 452 pre-built alphas for reproducible research and gated agentic trading.
AI Agent2026
Provides a lightweight Python harness that turns LLMs into working agents with tool-use, skills, persistent memory, permission controls and multi-agent coordination. Ships with a CLI/React TUI, 43+ built-in tools, a plugin/skill system and the ohmo personal-agent for chat gateways. Best for developers prototyping agent workflows and multi-agent experiments.