A

ai-agents

Kahin;hibrit bir cdp ansiklopedisi ve anti-detect browser otomasyon mcpsidir. Yerleşik olarak obscura ve camoufox kullanır,dinamik olarak göreve göre seçer. Seçimi ajanınız yapar.

https://www.npmjs.com/package/@kahinmcp/kahin

Multi-platform AI dev-team orchestration with a single canonical knowledge base. Plan-Approve-Execute workflows, validation gates, projected to GitHub Copilot, Gemini CLI, Opencode, and Cursor.

icarus is a CLI AI coding agent built on the daedalus framework. It is an autonomous coding agent that can explore repositories, read and write files, run shell commands, and call tools — either interactively from the terminal or as a subprocess driven by an IDE.

An autonomous agent library for C++23. It ships as libdaedalus.a plus four worked example hosts (demos/). Embed it in any C++23 host (CLI, web, IDE plugin, CI bot) and drive one or more Agent instances via the public API. See docs/embedding.md to get started.

A Coinbase x402 micropayment-gated API proxy for The Undesirables TCG Oracle. Allows AI agents to semantically discover and autonomously pay for physical trading card grading and Monte Carlo market intelligence using USDC on the Base network. Fully integrated with the CDP Bazaar Discovery layer.

Seven evidence-first tools for bounded AI-agent decisions, resumable runs, cross-agent handoffs, verification, and reviewable releases.

A native desktop AI code editor written in C++23 with GTK4 / gtkmm — a GTK4 port of a previously browser-based UI. The full behavioral specification lives in docs/design.md.

An AI ecosystem radar that detects structural shifts in open-source AI by analyzing GitHub, Hacker News, and Reddit, then clustering signals into long-term patterns.

A structured second brain for AI-enabled product work. This guide teaches your AI assistant how to help you organize, track, and sustain work on any product — software, business plans, research projects, or anything else that benefits from structured context and incremental progress.

Concurrent Workspace & Swarm Orchestrator — a deterministic Go-kernel MCP backend orchestrating LLM sub-agent swarms in ephemeral in-memory Git Shadow Workspaces with semantic AST merge.

CI agent platform generalized from 20k~ line repo

PersonaLock is an open source, identity-first AI platform that preserves a user's authentic voice, reasoning, values, and evidence standards across every interaction. Built around a native identity-aware language model with integrated research and writing capabilities, it archives and learns from user-approved publications while preventing drift through transparent, explainable governance. Instead of simply generating content, PersonaLock ensures every output remains faithful to the person behind it. https://roxanneardary.com/personalock/

Cognitive exoskeleton for AI agents and human researchers — by Cognitive Functors. Turn questions into verified constructive & destructive insights: breakthrough scientific-engineering hypotheses checked across 47 literature sources, 38 simulation bridges, and 9 formal verifiers — then gated proposals, dissertations, BibTeX, and proofs you can publish. Not a chatbot — a research pipeline. pip install c4reqber · blast solve · Z₃³ · 21 MCP · AGPL-3.0.

db-gateway-mcp is an MCP server that lets AI coding agents securely interact with MySQL/MariaDB databases across multiple systems and environments—supporting schema inspection, stored procedure discovery, controlled query execution, and future migration automation workflows.

Know your user: a USER.md that grows. Your AI's understanding of you in a file you own — hand-written lane + agent-curated lane, no silent rewrites, moves when your folder moves.

A predictions ledger with forced settlement for AI agents: log every judgment as a bet, settle it against reality, distill recurring biases into rules. Learns from outcomes, not corrections.

Local-first, human-in-the-loop AI hiring assistant (v0.5, recruiting module only). 本地优先、人在环的 AI 招聘决策辅助。

Real-world AI usage playbook: what actually works, from daily hands-on use. lucio 的 AI 实战手记（中文）。

Route each subagent to the cheapest capable model - about 70% off execution-tier tokens in our tests (Claude Code / any multi-tier agent platform)

Teach your AI agent to acquire capabilities on its own - find existing skills before building one (Claude Code / any LLM)