# #agents — MDRSS hashtag feed

> Public MDRSS cards tagged #agents.
> Canonical feed: https://mdrss.com/feeds/agents

## Cards (61)

### [LangChain & LangGraph Architecture](https://mdrss.com/ai-agents/agent-design-and-orchestration/901343/901343.md)

Master modern LangChain 1.x and LangGraph for building sophisticated LLM applications with agents, state management, memory, and tool integration. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — TypeScript](https://mdrss.com/ai-agents/agent-design-and-orchestration/901155/901155.md)

List files the agent wrote to /mnt/session/outputs/ during a session, then. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Webhooks](https://mdrss.com/ai-agents/agent-design-and-orchestration/901149/901149.md)

Anthropic can POST to your HTTPS endpoint when a Managed Agents resource changes state — an alternative to holding an SSE stream or polling. Payloads are thin (event type + resource IDs only); on receipt, fetch the resource for current state. Every delivery is HMAC-signed. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Tools & Skills](https://mdrss.com/ai-agents/agent-design-and-orchestration/901148/901148.md)

Override defaults for individual tools. This example enables everything except bash:. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Self-Hosted Sandboxes](https://mdrss.com/ai-agents/agent-design-and-orchestration/901147/901147.md)

With config.type: "self hosted", the agent loop stays on Anthropic's orchestration layer but tool execution moves to infrastructure you control — bash, file ops, and code run inside your container, so filesystem contents and network egress never leave your environment. Use it as a repeatable review, validation or hardening pass.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Scheduled Deployments](https://mdrss.com/ai-agents/agent-design-and-orchestration/901146/901146.md)

A scheduled deployment runs an agent on a recurring cron schedule — each firing creates a session autonomously. Use it for predictable-cadence work: nightly triage, weekly compliance scans, hourly monitors. Use it as a repeatable review, validation or hardening pass.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Overview](https://mdrss.com/ai-agents/agent-design-and-orchestration/901145/901145.md)

Managed Agents provisions a container per session as the agent's workspace. The agent loop runs on Anthropic's orchestration layer; the container is where the agent's tools execute — bash commands, file operations, code. You create a persisted Agent config (model, system pr. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Outcomes](https://mdrss.com/ai-agents/agent-design-and-orchestration/901144/901144.md)

An outcome elevates a session from conversation to work : you state what "done" looks like, and the harness runs an iterate → grade → revise loop until the artifact meets the rubric, hits max iterations, or is interrupted. A separate grader (independent context windo. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Onboarding Flow](https://mdrss.com/ai-agents/agent-design-and-orchestration/901143/901143.md)

Claude Managed Agents is a hosted agent: Anthropic runs the agent loop and provisions a sandboxed container per session where the agent's tools execute (or your own worker, with a self hosted environment — see shared/managed-agents-self-hosted-sandboxes.md). You supply an a. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Multiagent Sessions](https://mdrss.com/ai-agents/agent-design-and-orchestration/901142/901142.md)

A coordinator agent can delegate to other agents within one session. All agents share the container and filesystem ; each runs in its own thread — a context-isolated event stream with its own conversation history, model, system prompt, tools, MCP servers, and skills (from. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Memory Stores](https://mdrss.com/ai-agents/agent-design-and-orchestration/901141/901141.md)

Sessions are ephemeral by default — when one ends, anything the agent learned is gone. A memory store is a workspace-scoped collection of small text documents that persists across sessions. When a store is attached to a session (via resources ), it is mounted into the cont. Use it as a repeatable review, validation or hardening pass.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Events & Steering](https://mdrss.com/ai-agents/agent-design-and-orchestration/901140/901140.md)

Send events to a session via POST /v1/sessions/{id}/events. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Environments & Resources](https://mdrss.com/ai-agents/agent-design-and-orchestration/901139/901139.md)

Creating a session requires an environment id. Environments are reusable configuration templates for spinning up containers in Anthropic's infrastructure — you might create different environments for different use cases (e.g. data visualization vs web development, with diff. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Core Concepts](https://mdrss.com/ai-agents/agent-design-and-orchestration/901138/901138.md)

Every session has a live trace view in the Anthropic Console at https://platform.claude.com/workspaces/{workspace}/sessions/{session id}. Print this URL immediately after creating a session so the user can watch tool calls and messages stream in real time. {workspace} is th. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Common Client Patterns](https://mdrss.com/ai-agents/agent-design-and-orchestration/901137/901137.md)

Patterns you'll write on the client side when driving a Managed Agent session, grounded in working SDK examples. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Endpoint Reference](https://mdrss.com/ai-agents/agent-design-and-orchestration/901136/901136.md)

All endpoints require x-api-key and anthropic-version: 2023-06-01 headers. Managed Agents endpoints additionally require the anthropic-beta header. Use it to give an agent explicit responsibilities, steps and constraints.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Agent Design Patterns](https://mdrss.com/ai-agents/agent-design-and-orchestration/901132/901132.md)

This file covers decision heuristics for building agents on the Claude API: which primitives to reach for, how to design your tool surface, and how to manage context and cost over long runs. For per-tool mechanics and code examples, see tool-use-concepts.md and the language-spe. Use it as a repeatable review, validation or hardening pass.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Managed Agents — Python](https://mdrss.com/ai-agents/agent-design-and-orchestration/901131/901131.md)

List files the agent wrote to /mnt/session/outputs/ during a session, then. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [CoALA: Awesome Language Agents](https://mdrss.com/ai-agents/agent-design-and-orchestration/901127/901127.md)

A compilation of language agents using the Cognitive Architectures for Language Agents (🐨CoALA) framework. - CoALA Paper (16 pages of main content): https://arxiv.org/abs/2309.02427 - CoALA Tweet (6 threads): https://twitter.com/ShunyuYao12/status/1699396834983362690 - CoALA. Use it to navigate the topic and choose relevant methods, papers or tools.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Learn Claude Code -- Harness Engineering for Real Agents](https://mdrss.com/ai-agents/agent-design-and-orchestration/901111/901111.md)

At the core of every agent is a neural network -- a Transformer, an RNN, a trained function -- shaped by billions of gradient updates on sequences of perception, reasoning, and action. Agency was never bestowed by the surrounding code. It was learned during training. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Awesome OpenClaw Agents](https://mdrss.com/ai-agents/agent-design-and-orchestration/901087/901087.md)

Pick a template, see what it does, get a Dockerfile + docker-compose + bot + README you can run anywhere. Use it as a repeatable review, validation or hardening pass.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Contents](https://mdrss.com/ai-agents/agent-design-and-orchestration/901054/901054.md)

The most comprehensive list of AI agents, frameworks, and tools in 2026. 340+ resources across 20+ categories. Updated monthly. Use it to navigate the topic and choose relevant methods, papers or tools.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [GitNexus](https://mdrss.com/ai-agents/agent-design-and-orchestration/901043/901043.md)

Indexes any codebase into a knowledge graph — every dependency, call chain, cluster, and execution flow — then exposes it through smart MCP tools so AI agents never miss code. Use it to ground design choices in named patterns, trade-offs and examples.

Classification: ai-agents/agent-design-and-orchestration · Feed: ai-agents · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Claude Design System Prompt](https://mdrss.com/ai-agents/coding-agents/2366/2366.md)

Reverse-engineered system prompt of Claude Design from Anthropic. A system prompt and skill library that turns an LLM into an opinionated, accessibility-aware, AI-slop-resistant design collaborator.

Classification: ai-agents/coding-agents · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [metaswarm](https://mdrss.com/ai-agents/coding-agents/2324/2324.md)

A self-improving multi-agent orchestration framework for Claude Code, Gemini CLI, and Codex CLI. Coordinate 18 specialized AI agents and 13 orchestration skills through a complete software development lifecycle, from issue to merged PR, with recursive orchestration, parallel review gates, and a git-native knowledge base.

Classification: ai-agents/coding-agents · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Agent Starter for React](https://mdrss.com/ai-agents/agent-frameworks/2239/2239.md)

This is a starter template for LiveKit Agents that provides a simple voice interface using Agents UI components and LiveKit JavaScript SDK. It supports voice, transcriptions, and virtual avatars.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [HomeRail](https://mdrss.com/ai-agents/agent-frameworks/2231/2231.md)

English | 中文 HomeRail is a TypeScript runtime that turns one-off agent chats into auditable, reusable workflows. The name comes from what it is: Home — it runs on your own homelab, NAS, or home server, serving the people who live there; Rail — the track shape of a DAG, where agent work flows node to node along explicit edges instead of pooling in a single chat.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Resume Skills for Claude Code](https://mdrss.com/ai-agents/coding-agents/2204/2204.md)

A collection of AI agent skills focused on resume optimization, job applications, and career development. Built for job seekers, career changers, and professionals who want Claude Code to help with resume writing, ATS optimization, interview prep, and strategic job search.

Classification: ai-agents/coding-agents · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Context+](https://mdrss.com/ai-agents/mcp-and-tools/2155/2155.md)

Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Steps to Set Up the Library](https://mdrss.com/ai-agents/prompting/2071/2071.md)

Prompt with an image/video → Get runnable vision code → Build Visual AI App in minutes Discord · Architecture · YouTube VisionAgent is the Visual AI pilot from LandingAI. Give it a prompt and an image, and it automatically picks the right vision models and outputs ready‑to‑run code—letting you build vision‑enabled apps in minutes.

Classification: ai-agents/prompting · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [AgenticGoKit](https://mdrss.com/ai-agents/agent-frameworks/2039/2039.md)

Robust Go framework for building intelligent multi-agent AI systems The most productive way to build AI agents in Go. AgenticGoKit provides a unified, streaming-first API for creating intelligent agents with built-in workflow orchestration, tool integration, and memory management.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [PRP (Product Requirement Prompts)](https://mdrss.com/ai-agents/prompting/2019/2019.md)

A collection of prompts for AI-assisted development with Claude Code. https://www.youtube.com/watch?v=KVOZ9s1S9Gk&lc=UgzfwxvFjo6pKEyPo1R4AaABAg Found value in these resources?

Classification: ai-agents/prompting · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Model Context Protocol servers](https://mdrss.com/ai-agents/mcp-and-tools/2000/2000.md)

This repository is a collection of reference implementations for the Model Context Protocol (MCP), as well as references to community-built servers and additional resources. The servers in this repository showcase the versatility and extensibility of MCP, demonstrating how it can be used to give Large Language Models (LLMs) secure, controlled access to tools and data sources.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [PSAI](https://mdrss.com/ai-agents/mcp-and-tools/1994/1994.md)

• Documentation • PowerShell-Native AI Agents & Multi-Agent Orchestration PSAI is a high-agency framework designed to bridge the gap between robust systems engineering and Large Language Models. Built for developers and architects, it transforms AI from a "chatbot" into a functional engineering component within your existing PowerShell ecosystem.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [PromptLayer](https://mdrss.com/ai-agents/prompting/1923/1923.md)

Version, test, and monitor every prompt and agent with robust evals, tracing, and regression sets. --- This library provides convenient access to the PromptLayer API from applications written in python.

Classification: ai-agents/prompting · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [ade-cli](https://mdrss.com/software-craft/developer-tooling/1879/1879.md)

Agentic Document Extraction (ADE), from your terminal. The ade command drives LandingAI's ADE v2 document APIs — parse turns visually complex documents (tables, figures, charts) into grounded markdown and elements; extract pulls schema-shaped fields with page-and-box evidence — and persists everything it produces in a local store (~/.ade), serving every read from it.

Classification: software-craft/developer-tooling · Feed: software-craft · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [go-agent](https://mdrss.com/ai-agents/agent-frameworks/1856/1856.md)

go-agent is a Go framework for building AI agents with pluggable LLM providers, memory, file context, guardrails, UTCP tool orchestration, and multi-agent coordination. Use it when you want agent runtime pieces that stay idiomatic in Go: For this repository: The module currently targets Go 1.25.10.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Key Features](https://mdrss.com/ai-agents/agent-frameworks/1788/1788.md)

Solace Agent Mesh Open-source framework for building event driven multi-agent AI systems Star ⭐️ this repo to stay updated as we ship new features and improvements. Key Features • Quickstart • Next Steps • Docs --- Solace Agent Mesh is a framework that supports building AI applications where multiple specialized AI agents work together to solve complex problems.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Agentic Document Extraction Python Library](https://mdrss.com/ai-agents/agent-frameworks/1759/1759.md)

) Docs · Playground · LandingAI The official Python library for the LandingAI Agentic Document Extraction (ADE) API. Parse PDFs and images into structured, grounded Markdown, then extract typed fields with a JSON Schema or Pydantic model.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Dash](https://mdrss.com/ai-agents/agent-frameworks/1752/1752.md)

A self-learning data agent built with systems engineering principles. It grounds answers in 6 layers of context and improves with every query.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Instructor Php](https://mdrss.com/ai-agents/agent-frameworks/1575/1575.md)

This monorepo contains a set of dev-friendly, framework agnostic components offering 3 main capabilities: Framework integration packages: The library offers a set of small, focused building blocks. Purpose: turn messy model output into typed PHP data.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Startup Founder Skills for AI Agents](https://mdrss.com/growth/product-growth-and-gtm/1528/1528.md)

I've been bootstrapping and starting companies for the past 10 years (still working hard at 996 level). Somewhere along the way, I realized that more and more of what I do every day — writing cold emails, drafting pitch decks, prepping for calls, reviewing contracts, writing job descriptions — can be automated.

Classification: growth/product-growth-and-gtm · Feed: growth · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Openhuman](https://mdrss.com/ai-agents/agent-frameworks/1455/1455.md)

OpenHuman OpenHuman is your personal AI super intelligence: a brain that remembers everything, a fantastic orchestrator, a deep researcher. Discord • Reddit • X/Twitter • Docs • Follow @senamakel (Creator) 🇺🇸 English | 🇨🇳 简体中文 | 🇯🇵 日本語 | 🇰🇷 한국어 | 🇩🇪 Deutsch | 🇵🇰 اردو Download installers from tinyhumans.ai/openhuman or from the GitHub Releases page.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [TradingView MCP Bridge](https://mdrss.com/ai-agents/mcp-and-tools/1404/1404.md)

Personal AI assistant for your TradingView Desktop charts. Connects Claude Code to your locally running TradingView app via Chrome DevTools Protocol for AI-assisted chart analysis, Pine Script development, and workflow automation.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [LazyLLM: A Low-code Development Tool For Building Multi-agent LLMs Applications](https://mdrss.com/ai-agents/agent-frameworks/1376/1376.md)

中文 | EN LazyLLM is a low-code development tool for building multi-agent large language model applications. It assists developers in creating complex AI applications at very low costs and enables continuous iterative optimization.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [GitMCP](https://mdrss.com/ai-agents/mcp-and-tools/1319/1319.md)

What is GitMCP • Features • Getting Started • How It Works • Badge • Examples • FAQ • Privacy • Contributing • License Stop vibe-hallucinating and start vibe-coding! GitMCP is a free, open-source, remote Model Context Protocol (MCP) server that transforms any GitHub project (repositories or GitHub pages) into a documentation hub.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [PAL MCP: Many Workflows. One Context](https://mdrss.com/ai-agents/mcp-and-tools/1295/1295.md)

A Model Context Protocol server that supercharges tools like Claude Code, Codex CLI, and IDE clients such as Cursor or the Claude Dev VS Code extension. PAL MCP connects your favorite AI tool to multiple AI models for enhanced code analysis, problem-solving, and collaborative development.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Awesome MCP Servers](https://mdrss.com/ai-agents/mcp-and-tools/1288/1288.md)

These servers aim to demonstrate MCP features and the TypeScript and Python SDKs. Official integrations are maintained by companies building production ready MCP servers for their platforms.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Awesome Remote MCP Servers](https://mdrss.com/ai-agents/mcp-and-tools/1249/1249.md)

A curated, opinionated list of high-quality remote Model Context Protocol (MCP) servers. This repository focuses on listing official and well-maintained MCP servers that can be accessed over the internet, helping developers discover reliable and production-ready services for their AI applications.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [What is MatrixOne?](https://mdrss.com/platforms/data-platforms/1235/1235.md)

Docs || Official Website || Research Paper English || 简体中文 Connect with us: Contents ======== MatrixOne is the industry's first database to bring Git-style version control to data, combined with MySQL compatibility, AI-native capabilities, and cloud-native architecture. At its core, MatrixOne is a HTAP (Hybrid Transactional/Analytical Processing) database with a hyper-converged HSTAP engine that seamlessly handles transactional (OLTP), analytical (OLAP), full-text search, and

Classification: platforms/data-platforms · Feed: platforms · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Swarm (experimental, educational)](https://mdrss.com/ai-agents/agent-frameworks/1213/1213.md)

Requires Python 3.10+ or Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions: Agents and handoffs.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Marketing Skills for AI Agents](https://mdrss.com/growth/ai-search-and-geo/1165/1165.md)

A collection of AI agent skills focused on marketing tasks. Built for technical marketers and founders who want AI coding agents to help with conversion optimization, copywriting, SEO, analytics, and growth engineering.

Classification: growth/ai-search-and-geo · Feed: growth · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [DESIGN.md](https://mdrss.com/ai-agents/agent-frameworks/1148/1148.md)

A format specification for describing a visual identity to coding agents. DESIGN.md gives agents a persistent, structured understanding of a design system.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Awesome MCP Servers](https://mdrss.com/ai-agents/mcp-and-tools/1038/1038.md)

A curated, community-driven list of awesome Model Context Protocol (MCP) servers, tools, frameworks, clients, and utilities. MCP is an open protocol that enables AI models to securely interact with local and remote resources through standardized server implementations.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [SwarmClaw](https://mdrss.com/ai-agents/agent-frameworks/1028/1028.md)

The self-hosted AI agent runtime and multi-agent framework for autonomous agents. Open-source agent swarms with durable agent memory, MCP tools, skills, delegation, schedules, and 23+ LLM providers — a practical Claude Code and LangChain alternative.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Query | MCP server for Supabase](https://mdrss.com/ai-agents/mcp-and-tools/1015/1015.md)

Query MCP is an open-source MCP server that lets your IDE safely run SQL, manage schema changes, call the Supabase Management API, and use Auth Admin SDK — all with built-in safety controls. Getting started • Feature overview • Troubleshooting • Changelog Installing the server requires the following on your system: If you plan to install via uv, ensure it's installed.

Classification: ai-agents/mcp-and-tools · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Open Deep Research](https://mdrss.com/ai-agents/agent-frameworks/999/999.md)

Deep research has broken out as one of the most popular agent applications. This is a simple, configurable, fully open source deep research agent that works across many model providers, search tools, and MCP servers.

Classification: ai-agents/agent-frameworks · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Cline](https://mdrss.com/software-craft/developer-tooling/989/989.md)

Cline The open source coding agent in your IDE and terminal. Docs Discord r/cline Feature Requests Join us!

Classification: software-craft/developer-tooling · Feed: software-craft · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Agentmemory](https://mdrss.com/ai-agents/coding-agents/890/890.md)

Built on iii engine Persistent memory for Claude Code, GitHub Copilot CLI, Cursor, Gemini CLI, Codex CLI, Hermes, OpenClaw, pi, OpenCode, and any MCP client. English | 简体中文 | 繁體中文 | 日本語 | 한국어 | Español | Türkçe | Русский | हिन्दी | Português | Français | Deutsch The gist extends Karpathy's LLM Wiki pattern with confidence scoring, lifecycle, knowledge graphs, and hybrid search: agentmemory is the implementation.

Classification: ai-agents/coding-agents · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Lobster](https://mdrss.com/software-craft/developer-tooling/888/888.md)

An OpenClaw-native workflow shell: typed (JSON-first) pipelines, jobs, and approval gates. OpenClaw (or any other AI agent) can use lobster as a workflow engine and avoid re-planning every step — saving tokens while improving determinism and resumability.

Classification: software-craft/developer-tooling · Feed: software-craft · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Brex's Prompt Engineering Guide](https://mdrss.com/ai-agents/prompting/814/814.md)

This guide was created by Brex for internal purposes. It's based on lessons learned from researching and creating Large Language Model (LLM) prompts for production use cases.

Classification: ai-agents/prompting · Feed: ai-agents · Updated: 2026-08-04T12:22:38.168Z · Version: 1