⚡ Awesome Agentic Patterns & Production Playbook

A curated collection of battle-tested AI Agent architectures, Model Context Protocol (MCP) servers, system prompt blueprints, context window optimization strategies, and ready-to-use rule templates for production software engineering.

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📑 Table of Contents

• Architectural Patterns
  • 1. Supervisor / Hierarchical Delegation
  • 2. Peer-to-Peer Swarm / Handoff
  • 3. Plan-and-Execute (Planner + Workers)
  • 4. Reflection & Evaluator-Optimizer
• Curated Model Context Protocol (MCP) Directory
• Ready-to-Use Agent Configuration Blueprints
  • Cursor (.cursorrules)
  • Claude Code (CLAUDE.md)
  • Google Antigravity (AGENTS.md)
  • Windsurf (.windsurfrules)
• Context Window & Token Economics
• Interactive Setup CLI
• Contributing
• License

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🏛️ Architectural Patterns

                          ┌───────────────────────┐
                          │   USER PROMPT / TASK  │
                          └───────────┬───────────┘
                                      │
                                      ▼
                      ┌───────────────────────────────┐
                      │    SUPERVISOR / ROUTER AGENT  │
                      └───────┬───────────────┬───────┘
                              │               │
             ┌────────────────▼───┐       ┌───▼────────────────┐
             │ RESEARCH SUBAGENT  │       │ CODING SUBAGENT    │
             │ (Read-Only Tools)  │       │ (Read/Write/Exec)  │
             └────────────────┬───┘       └───┬────────────────┘
                              │               │
                              └───────┬───────┘
                                      │
                                      ▼
                      ┌───────────────────────────────┐
                      │     EVALUATOR & VERIFIER      │
                      └───────────────────────────────┘

1. Supervisor / Hierarchical Delegation

• When to use: Complex workflows where a primary agent breaks problems into sub-problems and delegates to specialized subagents.
• Benefits: Prevents context window dilution. The root agent receives only distilled summaries while subagents perform noisy intermediate tasks (e.g., searching 50 files or parsing massive logs).
• Reference Template: templates/antigravity/AGENTS.md

2. Peer-to-Peer Swarm / Handoff

• When to use: Multi-domain tasks where execution flow transitions statefully (e.g., Triage Agent $\to$ Billing Agent $\to$ Technical Agent).
• Benefits: Decentralized control; agents hand off control via structured function calling (transfer_to_billing()).

3. Plan-and-Execute (Planner + Workers)

• When to use: Long-running coding refactors or multi-module migrations.
• Pattern:
  1. Planner Agent: Creates an explicit step-by-step checklist (task.md).
  2. Worker Agents: Pick up sequential tasks and report status.
  3. Verification Step: Runs unit tests and linter before marking steps as completed.

4. Reflection & Evaluator-Optimizer

• When to use: Generating code, database security rules, or high-reliability API schemas.
• Pattern: Generator agent outputs draft $\to$ Critic/Auditor agent evaluates against security checklist $\to$ Generator applies targeted corrections.

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🔌 Curated Model Context Protocol (MCP) Directory

The Model Context Protocol (MCP) standardizes how AI agents communicate with external tools and data sources. Below are production-ready MCP servers:

MCP Server	Category	Description	Command / Source
mcp-server-filesystem	Filesystem	Secure, constrained file reading & editing	npx -y @modelcontextprotocol/server-filesystem /path
mcp-server-git	Version Control	Inspect diffs, commits, branches, and git logs	uvx mcp-server-git
mcp-server-postgres	Database	Read schemas and execute read-only queries	npx -y @modelcontextprotocol/server-postgres <conn-string>
mcp-server-github	Cloud / DevOps	Manage issues, pull requests, and discussions	npx -y @modelcontextprotocol/server-github
mcp-server-sqlite	Database	Local SQLite database introspection	uvx mcp-server-sqlite --db-path <path>
mcp-server-puppeteer	Web Automation	Browser navigation, screenshots, and scraping	npx -y @modelcontextprotocol/server-puppeteer
chrome-devtools-mcp	DevTools	Web performance, DOM inspection, and console audit	npx -y @chrome-devtools/mcp-server

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🛠️ Ready-to-Use Agent Configuration Blueprints

Cursor (.cursorrules)

Store in your repository root as .cursorrules:

# Role & Philosophy
You are an expert senior software engineer. Prioritize clean architecture, strict typing, and minimal regressions.

# Coding Guidelines
- Maintain documentation integrity: Never strip existing comments or docstrings.
- Always prefer pure functions and immutable data transformations.
- In TypeScript: Use strict mode, avoid `any`, prefer discriminated unions over enums.
- Always include automated test cases for edge conditions.

Claude Code (CLAUDE.md)

Store in your repository root as CLAUDE.md:

# Project Overview
Production service built with TypeScript & Node.js.

# Commands
- Build: `pnpm build`
- Test: `pnpm test`
- Lint: `pnpm lint --fix`

# Architecture Rules
- Controllers handle HTTP routing; services handle business logic; repositories handle data access.
- All database queries must use prepared statements and connection pooling.

Google Antigravity (AGENTS.md)

Store in your repository root as AGENTS.md:

# Agent Directives
- Prefer interactive sidecar viewers for visualization tasks.
- Keep context lean: Use subagents for broad codebase research and log scraping.
- Verify every modification with unit tests before declaring completion.

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📊 Context Window & Token Economics

Managing context windows is critical for agent reliability and cost efficiency:

1. The 60% Threshold: Once an agent's context window exceeds 60% capacity, instruction following accuracy begins to degrade exponentially.
2. Subagent Offloading: Delegate noisy operations (e.g. searching 50 files or reviewing 1,000 log lines) to short-lived subagents that return only a 3-sentence summary.
3. Structured Artifacts: Persist long-term plans and state in markdown artifacts (task.md) rather than keeping the entire conversational history in memory.

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🚀 Interactive Setup CLI

Initialize agent rules and MCP configs for your project in seconds:

# Clone the repository
git clone https://github.com/DYNOSuprovo/awesome-agentic-patterns.git

# Run the setup wizard
python awesome-agentic-patterns/scripts/setup_agent.py

The CLI inspects your workspace, detects whether you use Next.js, Python, Node, Go, or Rust, and generates production-ready .cursorrules, CLAUDE.md, and mcp.json automatically!

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🤝 Contributing

Contributions are welcomed! Have a new MCP server, production prompt pattern, or architecture diagram?

1. Fork the repo.
2. Create your feature branch (git checkout -b feature/new-pattern).
3. Commit your changes (git commit -m 'Add Multi-Agent Reflection blueprint').
4. Push to the branch (git push origin feature/new-pattern).
5. Open a Pull Request.

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📄 License

Distributed under the MIT License. See LICENSE for more information.