# Multi Agent > The definitive catalog of AI agent patterns. One definition, any framework. 27+ agents, 8 patterns, 6 framework adapters. - **Type:** MCP server - **Install:** `agentstack add mcp-hovborg-multi-agent` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [Hovborg](https://agentstack.voostack.com/s/hovborg) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Hovborg](https://github.com/Hovborg) - **Source:** https://github.com/Hovborg/multi-agent ## Install ```sh agentstack add mcp-hovborg-multi-agent ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About 简体中文 • 日本語 • 한국어 • Español • Deutsch • Dansk multi-agent The definitive catalog of AI agent patterns. One definition, any framework. Quick Start • Agent Catalog • Smart Enhancements • Patterns • Playground • Docs • Contributing --- **48 catalog agent definitions. 11 categories. 8 orchestration patterns. 6 framework adapters. 8 export targets. Zero lock-in.** `multi-agent` is a framework-agnostic catalog of production-ready AI agent patterns. Define your agents once in YAML, run them on CrewAI, LangGraph, OpenAI Agents SDK, Claude SDK, Google ADK, or smolagents. Stop reinventing agents. Start composing them. ## Why multi-agent? | | multi-agent | CrewAI | LangGraph | OpenAI SDK | Claude SDK | |---|:---:|:---:|:---:|:---:|:---:| | Framework-agnostic definitions | **Yes** | No | No | No | No | | Export to any AI platform | **Yes** | No | No | No | No | | Reusable agent catalog | **Yes** | Framework-specific | Framework-specific | Framework-specific | Framework-specific | | Pattern library (8 patterns) | **Yes** | 2 | 3 | 2 | 2 | | Built-in cost estimation | **Yes** | No | No | No | No | | Agent recommendation engine | **Yes** | No | No | No | No | | Works with any LLM | **Yes** | Yes | Yes | OpenAI only | Claude only | | MCP native | **Yes** | Partial | Adapter | Yes | Yes | ## Quick Start ```bash pip install multi-agent ``` ### 1. Browse the catalog ```bash multiagent search "code review" ``` ``` Found 3 agents matching "code review": code/code-reviewer Review PRs for bugs, style, and security code/test-writer Generate tests for changed code code/refactorer Suggest and apply refactoring improvements Recommended pattern: supervisor-worker (1 reviewer + N specialists) Estimated cost: ~$0.03/review (Claude Haiku) to ~$0.25/review (GPT-4o) ``` ### 2. Use an agent definition ```python from multiagent import Catalog, patterns # Load agents from the catalog catalog = Catalog() reviewer = catalog.load("code/code-reviewer") test_writer = catalog.load("code/test-writer") # Describe a portable pattern; execution belongs to a framework adapter team = patterns.supervisor_worker( supervisor=reviewer, workers=[test_writer], model="claude-sonnet-4-6" # or any model ) print(team.describe()) ``` ### 3. Or use with your favorite framework ```python # Build a framework-neutral OpenAI agent-as-tool plan without importing its SDK from multiagent.adapters import openai_sdk plan = openai_sdk.to_agent_tool_config(reviewer, [test_writer]) # Optional runtime adapters create native objects when their extras are installed # pip install "multi-agent[openai]" agent = openai_sdk.from_catalog("code/code-reviewer") # from agents import Runner # result = Runner.run_sync(agent, "Review this code") ``` ### 4. Export to any AI platform ```bash # Export for Claude Code (.claude/agents subagents) multiagent export code/code-reviewer claude-code -o .claude/agents # Export as a portable AgentSkills-style SKILL.md file multiagent export code/code-reviewer agentskill -o .agents/skills/code-reviewer # Export as an A2A Agent Card JSON document multiagent export code/code-reviewer a2a-agent-card -o ./agent-cards # Export for Codex / OpenClaw (AGENTS.md format) multiagent export code/code-reviewer codex # Export for Codex project config (.codex/config.toml snippet) mkdir -p .codex multiagent export code/code-reviewer codex-config > .codex/config.toml # Export for Google Gemini / ADK multiagent export code/code-reviewer gemini -o ./adk-agents # Export for ChatGPT (Custom GPT instructions) multiagent export code/code-reviewer chatgpt # Export just the system prompt (works with ANY LLM) multiagent export code/code-reviewer raw # Bulk export all agents in a category multiagent export-all claude-code -o .claude/agents -c code ``` | Target | Format | Works With | |--------|--------|------------| | `claude-code` | `.md` subagent files | Claude Code `.claude/agents/` | | `agentskill` | `SKILL.md`-style Markdown | AgentSkills-compatible tools | | `a2a-agent-card` | Agent Card JSON | A2A discovery via `.well-known/agent-card.json` | | `codex` | AGENTS.md sections | OpenAI Codex, OpenClaw | | `codex-config` | `.codex/config.toml` snippet | OpenAI Codex multi-agent roles | | `gemini` | ADK YAML config | Google Gemini, Vertex AI | | `chatgpt` | System instructions | ChatGPT, Custom GPTs | | `raw` | Plain system prompt | **Any LLM** — Ollama, LM Studio, llama.cpp, vLLM, etc. | ### Route before exporting ```bash # Dry-run agent selection and include export commands for the chosen target multiagent route "review this PR and write missing tests" --target a2a-agent-card # Machine-readable route decision with target export plan multiagent route "review this PR and write missing tests" --target codex-config --json # Regression-test the built-in routing corpus multiagent eval-routing --json # CI-friendly score gates; target hints may evolve faster than agent matching multiagent eval-routing \ --min-agent-score 1.0 \ --min-pattern-score 1.0 \ --min-target-score 0.95 \ --min-forbidden-score 1.0 \ --min-risk-score 1.0 \ --min-context-score 1.0 \ --min-policy-score 1.0 # Validate all schemas, slugs, duplicate names, and cross-agent references multiagent validate # Route directly into a framework-native plan instead of a file export multiagent route "review this PR and write missing tests" --target openai-agents --json multiagent route "research three sources with Google ADK" --target adk --json ``` Route JSON includes `risk`, `context`, and `policy` blocks. The policy makes control mode, bounded fan-out, delegation contracts, trust boundaries, approval requirements, and stop conditions explicit. This command is a dry run: it never executes an agent or contacts a model provider. See [08 -- Human Review Gates](cookbook/08-human-review-gates.md) and [09 -- Safe Delegation Policy](cookbook/09-safe-delegation-policy.md). ## Agent Catalog Every agent is defined in a simple, readable YAML format: ```yaml # src/multiagent/catalog_data/code/code-reviewer.yaml name: code-reviewer version: "1.0" description: Reviews code changes for bugs, security issues, and style violations category: code system_prompt: | You are an expert code reviewer. Analyze the provided code changes and identify: 1. Bugs and logic errors 2. Security vulnerabilities (OWASP Top 10) 3. Performance issues 4. Style and readability improvements Be specific. Reference line numbers. Suggest fixes. tools: - type: mcp server: filesystem - type: function name: search_codebase description: Search for related code in the repository parameters: temperature: 0.1 max_tokens: 4096 cost_profile: tokens_per_run: ~2000 recommended_model: claude-haiku-4-5 # Best cost/quality for reviews estimated_cost_usd: 0.003 works_with: - code/test-writer # Generate tests for flagged code - code/refactorer # Apply suggested improvements recommended_patterns: - supervisor-worker # Reviewer supervises specialist agents - sequential # Review → Test → Refactor pipeline # Optional schema v2 metadata for routing, safety, observability, and protocols orchestration: control_mode: router execution_mode: dry_run safety: side_effect_risk: low requires_human_review: true observability: trace_tags: [code-review] eval_criteria: [finds-bugs, suggests-fixes] outputs: expected_artifacts: [review-comments] context: loading: trigger max_context_tokens: 4096 protocols: a2a: expose: true ``` ### Full Catalog | Category | Agents | Description | |----------|--------|-------------| | **[code/](src/multiagent/catalog_data/code/)** | `code-reviewer` `code-generator` `test-writer` `refactorer` `debugger` `security-auditor` `documentation-writer` `pr-summarizer` | Software development lifecycle | | **[research/](src/multiagent/catalog_data/research/)** | `deep-researcher` `web-scraper` `fact-checker` `paper-analyst` `competitive-intel` | Research and analysis | | **[data/](src/multiagent/catalog_data/data/)** | `data-analyst` `sql-generator` `report-writer` | Data engineering and analysis | | **[devops/](src/multiagent/catalog_data/devops/)** | `ci-cd-agent` `infra-provisioner` `monitoring-agent` `incident-responder` | Infrastructure and operations | | **[content/](src/multiagent/catalog_data/content/)** | `writer` `editor` `translator` `seo-optimizer` | Content creation pipeline | | **[finance/](src/multiagent/catalog_data/finance/)** | `trading-analyst` `portfolio-optimizer` `financial-reporter` `fraud-detector` `tax-advisor` | Financial analysis and compliance | | **[support/](src/multiagent/catalog_data/support/)** | `customer-support` `ticket-router` `knowledge-base-builder` `escalation-agent` | Customer service pipeline | | **[legal/](src/multiagent/catalog_data/legal/)** | `contract-reviewer` `legal-researcher` `compliance-checker` `document-drafter` | Legal and compliance | | **[personal/](src/multiagent/catalog_data/personal/)** | `email-assistant` `meeting-scheduler` `note-taker` `task-manager` | Personal productivity | | **[security/](src/multiagent/catalog_data/security/)** | `vulnerability-scanner` `log-analyzer` `access-reviewer` `incident-analyst` | Security operations | | **[orchestration/](src/multiagent/catalog_data/orchestration/)** | `task-router` `cost-optimizer` `quality-gate` | Meta-agents for coordination | ## Patterns Eight battle-tested orchestration patterns, each with runnable examples: ### Pattern Overview ``` ┌─────────────┐ │ Supervisor │ ── Pattern 1: Supervisor/Worker └──────┬──────┘ Central agent delegates to specialists ┌─────┼─────┐ ▼ ▼ ▼ [W1] [W2] [W3] [A] → [B] → [C] ── Pattern 2: Sequential Pipeline Linear chain of specialized agents ┌──→ [A] ──┐ │ │ ├──→ [B] ──┼──→ [Merge] ── Pattern 3: Parallel Fan-Out │ │ Independent tasks run concurrently └──→ [C] ──┘ [A] ←──→ [B] ── Pattern 4: Reflection/Loop Iterative refinement between agents [A] ──handoff──→ [B] ──handoff──→ [C] ── Pattern 5: Handoff Agent transfers full control ┌─[A]─┐ ── Pattern 6: Group Chat │ [B] │ ← Selector Shared conversation, dynamic speaker └─[C]─┘ [A]─┬─[B] ── Pattern 7: DAG (Directed Acyclic Graph) └─[C]──[D] Conditional branching and merging ┌Worktree1: [A]┐ ── Pattern 8: Split-and-Merge │Worktree2: [B]│→ Git Merge Isolated parallel work, merged at end └Worktree3: [C]┘ ``` | Pattern | When to Use | Complexity | Latency | Example | |---------|------------|:----------:|:-------:|---------| | [Supervisor/Worker](docs/patterns/supervisor-worker.md) | Complex tasks with clear subtasks | Medium | Medium | Code review team | | [Sequential](docs/patterns/sequential.md) | Step-by-step processing | Low | High | Content pipeline | | [Parallel](docs/patterns/parallel.md) | Independent tasks | Low | Low | Multi-source research | | [Reflection](docs/patterns/reflection.md) | Quality-critical output | Medium | Medium | Legal document drafting | | [Handoff](docs/patterns/handoff.md) | Escalation and routing | Low | Low | Customer support tiers | | [Group Chat](docs/patterns/group-chat.md) | Brainstorming, debate | High | High | Design review | | [DAG](docs/patterns/dag.md) | Complex conditional workflows | High | Variable | CI/CD pipeline | | [Split-and-Merge](docs/patterns/split-and-merge.md) | Large parallel code changes | Medium | Low | Multi-file refactoring | ## Frameworks `multi-agent` provides adapter modules for the main Python agent frameworks: | Framework | Adapter | Current scope | |-----------|---------|---------------| | [CrewAI](docs/frameworks/comparison.md) | `multiagent.adapters.crewai` | Agent/Crew conversion; Flow template config | | [LangGraph](docs/frameworks/comparison.md) | `multiagent.adapters.langgraph` | Node/flow config conversion | | [OpenAI Agents SDK](docs/frameworks/comparison.md) | `multiagent.adapters.openai_sdk` | Agent conversion; handoff and agent-as-tool plans | | [Claude Agent SDK](docs/frameworks/comparison.md) | `multiagent.adapters.claude_sdk` | Message/subagent config conversion | | [Google ADK](docs/frameworks/comparison.md) | `multiagent.adapters.google_adk` | ADK config conversion; sequential/parallel workflow plans | | [smolagents](docs/frameworks/comparison.md) | `multiagent.adapters.smolagents` | Agent config conversion; manager/managed-agent plans | Adapter template helpers return plain dictionaries, so they can be inspected, tested, or translated into framework code before any framework package is installed: ```python from multiagent import Catalog from multiagent.adapters import crewai, google_adk, openai_sdk, smolagents catalog = Catalog() reviewer = catalog.load("code/code-reviewer") test_writer = catalog.load("code/test-writer") handoff_plan = openai_sdk.to_handoff_config(reviewer, [test_writer]) tool_plan = openai_sdk.to_agent_tool_config(reviewer, [test_writer]) adk_parallel = google_adk.to_workflow_config([reviewer, test_writer], workflow="parallel") flow = crewai.to_flow_config([reviewer, test_writer], flow_name="CodeReviewFlow", human_feedback=True) manager = smolagents.to_manager_config(reviewer, [test_writer]) ``` The router can also emit framework-native dry-run plans directly: ```bash multiagent route "review this PR and write missing tests with OpenAI Agents SDK" \ --target openai-agents \ --json multiagent route "research three sources with Google ADK" --target adk --json multiagent route "build a deterministic CrewAI review flow" --target crewai-flow --json multiagent route "coordinate workers with smolagents" --target smolagents-manager --json ``` Don't see your framework? [Submit an adapter](CONTRIBUTING.md#adding-an-adapter). ## Protocol Support Built for the 2026 protocol stack: | Protocol | Purpose | Support | |----------|---------|:-------:| | **[MCP](docs/protocols/mcp.md)** (Model Context Protocol) | Agent ↔ Tool | Native | | **[A2A](docs/protocols/a2a.md)** (Agent-to-Agent) | Agent ↔ Agent | Native | | **[AG-UI](docs/protocols/ag-ui.md)** (Agent-to-UI) | Agent ↔ Frontend | Planned | ## Smart Enhancements Make any agent smarter with research-backed prompt engineering techniques: ```bash # Enhance with category-tuned profile multiagent enhance code/code-reviewer # Apply all 8 techniques multiagent enhance code/code-reviewer -p all # Enhance + export to Claude Code multiagent enhance code/code-reviewer -p all -t claude-code -o .claude/agents ``` | Enhancement | Effect | Source | |------------|--------|--------| | `reasoning` | +20% task completion | OpenAI SWE-bench | | `error_recovery` | 5-level retry hierarchy | Anthropic engineering | | `verification` | Self-check before output | Claude Code internal | | `confidence` | -40-60% hallucination | Academic research | | `tool_discipline` | Faster, fewer errors | OpenAI GPT-5.4 guide | | `failure_modes` | Avoids 6 anti-patterns | 120+ leaked prompts study | | `context_management` | Better long-running tasks | LangChain context engineering | | `information_priority` | Facts over guessing | Manus AI / Anthropic | ```python from multiagent import Catalog, enhance_agent catalog = Catalog() agent = catalog.load("code/code-reviewer") smart_agent = enhance_agent(agent, profile="all") # All 8 techniques applied ``` ## Agent Composition Visualizer Auto-generate Mermaid diagrams for agent teams: ```bash multiagent visualize code/code-reviewer code … ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [Hovborg](https://github.com/Hovborg) - **Source:** [Hovborg/multi-agent](https://github.com/Hovborg/multi-agent) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-hovborg-multi-agent - Seller: https://agentstack.voostack.com/s/hovborg - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.