Enables agents to query the Brave Search API across web, local, news, image, and video indexes through five MCP tools, returning consistent result details.

Enables agents to look up a library's Context7-compatible ID and fetch its current, version-specific documentation and code examples, optionally focused on a topic and capped at a chosen token budget.

Enables agents to list indices, read mappings, run query DSL and ES|QL searches, and inspect shards on an Elasticsearch cluster through its HTTP API.

Enables agents and terminal users to browse MongoDB databases and collections, run queries and aggregation pipelines, modify documents, manage indexes and collections, inspect statistics and logs, and explain query plans.

Enables agents and terminal users to inspect ClickHouse over HTTP by listing databases and tables and running guarded read-only SELECT queries without modifying data.

Enables MCP clients and AI agents to author, inspect, validate, and render PromoShot .promo projects over stdio, delegating rendering to the promo CLI.

Local MCP server that gives any AI agent safe desktop control on Windows, macOS and Linux. Reads the screen as text and structure (accessibility + OCR) and acts by element name, with screenshots as the last resort. Multi-monitor aware, verifies every action, one safety gate.

Test mode for your integrations, built for the way agents build. Local, stateful twins of GitHub, Slack, Stripe, Gmail and Linear, over REST and MCP.

Audit trail and traceability for AI agents. See what every coding agent did, block risky calls, ask a human for approval, and prove it with signed trust checks.

On PAR Dev's Software Factory CLI: takes a GitHub issue through plan, build and check with AI agents, then opens a ready-for-review PR.

🎨 Open-source design MCP server + shadcn/ui registry — AI design systems for Claude Code, Cursor, Codex, GitHub Copilot & any MCP client. 31 brand-grade themes (Linear, Stripe, Vercel, Notion, Apple, Supabase, Figma…) + design tokens, UI principles & WCAG rules. Install any component with one command.

Evidence-driven task orchestration with PO First for Claude Code, Kiro, Codex, DeepSeek Harness, Antigravity, OpenCode, Grok Build, GitHub Copilot, Hermes Agent and OpenClaw

MCP gateway and orchestrator: one local install fronts every MCP server for Claude Code, Cursor, and VS Code, loading tools on demand.

Enables an LLM to triage hard-to-extract Vue components by feeding it structured coupling analysis, dependency graphs, and design tokens, then generating decoupling suggestions with before/after code, composable wrappers for store-bound components, and full rewrite-and-extract operations.

Kindly Web Search MCP Server: Web search + robust content retrieval for AI coding tools (Claude Code, Codex, Cursor, GitHub Copilot, Gemini, etc.) and AI agents (Claude Desktop, OpenClaw, Hermes, etc.). Supports Serper, Tavily, and SearXNG.

Spec-Driven Development MCP Server, not just Vibe Coding

DSH插件市场 / DSH Plugin Marketplace: 在 DeepSeek Harness Web GUI 中一键浏览、安装与更新 GitHub topic:dsh-plugin 的全部插件 | browse, install & update all GitHub dsh-plugin plugins in the DSH Web GUI

Ruflo CLI - Enterprise AI agent orchestration with 60+ specialized agents, swarm coordination, MCP server, self-learning hooks, and vector memory for Claude Code

Self-Optimizing Neural Architecture (SONA) for Claude Flow — adaptive learning, trajectory tracking, pattern reuse, 7 RL algorithms (PPO/A2C/DQN/Q-Learning/SARSA/Decision Transformer/Curiosity), Flash Attention, MoE routing, LoRA, EWC++ for continual lear

Portable AI code quality reviews for Codex, Cursor, Copilot and other coding agents: six Agent Skills for architecture, technical debt, tests and remediation.

Battle-tested Claude Code, OpenAI Codex, Cursor configs, plugins, hooks and agents with Kimi, MiniMax and GLM API support.

Add MCP servers to your favorite coding agents with a single command.

Re-debugging Solved Failures? No Way. 500+ Evidence-graded fix lessons, One MCP Call-->https://misakanet.org

Bounded-autonomy plugin harness for agents. Intent to implementation: ready, then go.