CrewAI Orchestrator

MCP server that turns any LLM into a CrewAI orchestrator. 15 tools, prebuilt crew templates, and RAG engine with 266+ indexed docs.

📖 Documentation: English · Español

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⚡ Install

git clone https://github.com/ssolis-ti/crewai-mcp-hq.git
cd crewai-mcp-hq
uv sync

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🔌 Connect to MCP Clients

Hermes Agent

hermes mcp add crewai-orchestrator \
  --command "/path/to/crewai-mcp-hq/.venv/Scripts/python.exe"
  --args "-X utf8 -m crewai_mcp.server"

Claude Desktop / Cursor / Roo Code

{
  "mcpServers": {
    "crewai-orchestrator": {
      "command": "/path/to/crewai-mcp-hq/.venv/bin/python",
      "args": ["-m", "crewai_mcp.server"],
      "cwd": "/path/to/crewai-mcp-hq",
      "env": { "CREWAI_MCP_TRANSPORT": "stdio" }
    }
  }
}

Docker (SSE)

docker-compose up -d
# Available at http://localhost:8808/sse

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🧰 Tools (15)

Domain	Tools
Projects	crewai_create_project, crewai_install_deps, crewai_project_info
Templates	crewai_apply_template
Agents & Tasks	crewai_define_agent, crewai_define_task, crewai_edit_crew_py, crewai_kickoff
Flows	crewai_flow_plot, crewai_flow_run
Knowledge	crewai_query_knowledge, crewai_manage_memory
Observability	crewai_test_crew, crewai_train_crew, crewai_replay_task

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🧩 Prebuilt Crew Templates

Deploy a full team in one call — no per-agent setup:

crewai_create_project(name="my-mvp", project_type="crew")
crewai_apply_template(project_name="my-mvp", template_name="cyberops")
# agents.yaml, tasks.yaml, and crew.py ready to run

CyberOps — MVP Development Team

5-agent sequential crew. Input: project description. Output: PRD + architecture + code + docs + QA.

Agent	Role	Configurable
PRD_Architect	Requirements & user stories	LLM, tools, max_iter
System_Designer	Architecture (ADRs, C4, API)	LLM, tools, max_iter
AI_Developer	AI-first code (<100 lines/file)	LLM, tools, max_iter
Doc_Engineer	LLM-optimized documentation	LLM, tools, max_iter
QA_Reviewer	Quality audit & traceability	LLM, tools, max_iter

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🗺️ Deployment Workflow (with your AI assistant)

The logical order to deploy a team of agents using the MCP. Just tell your assistant "I need a team for X" and it handles the rest:

1. CREATE      crewai_create_project("my-team", "crew")
                ↓
2. TEMPLATE    crewai_apply_template("my-team", "cyberops")
                ↓
3. INSTALL     crewai_install_deps("my-team")
                ↓
4. KICKOFF     crewai_kickoff("my-team", inputs={...})
                ↓
5. ITERATE     crewai_test_crew / crewai_replay_task / crewai_train_crew

Step-by-step with your AI assistant

Step	What you say	Tool called
Research	"I need a team to build [project]"	crewai_query_knowledge — assistant researches CrewAI docs
Scaffold	"Create the project"	crewai_create_project — directory + pyproject.toml
Template	"Apply CyberOps template"	crewai_apply_template — agents + tasks + crew.py
Customize	"Change AI_Developer to use gpt-4"	crewai_edit_crew_py — per-agent LLM/tools config
Install	"Install dependencies"	crewai_install_deps — pip/uv sync
Run	"Execute the crew"	crewai_kickoff — agents work sequentially
Debug	"QA agent failed — retry it"	crewai_replay_task — resumes from failed task
Improve	"Test and train"	crewai_test_crew / crewai_train_crew

Building a custom team from scratch

No prebuilt template? Define agents and tasks one by one:

1. CREATE     crewai_create_project("my-custom", "crew")
2. AGENTS     crewai_define_agent("my-custom", "researcher", role="...")
              crewai_define_agent("my-custom", "writer", role="...")
3. TASKS      crewai_define_task("my-custom", "research", agent="researcher")
              crewai_define_task("my-custom", "write", agent="writer")
4. INSTALL    crewai_install_deps("my-custom")
5. KICKOFF    crewai_kickoff("my-custom", inputs={...})

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📚 Documentation Resources

URI	Content
crewai://docs/index	266+ docs across 31 categories
crewai://docs/concepts/agents	Specific documentation pages
crewai://docs/search/{query}	Keyword search
crewai://templates/index	Agent, crew & flow templates
crewai://templates/prebuilt/index	Full crew templates (CyberOps + extensible)

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🛡️ Robustness

• Auto-patch versions: crewai create outputs pre-release pins → auto-patched to >=1.14.0
• Name normalization: hyphens/underscores handled transparently
• Timeouts on all subprocess calls: 120s–1200s depending on operation
• Standardized CLI: always uv run crewai, no PATH dependency

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📁 Structure

src/crewai_mcp/
├── server.py           ← Entry point (stdio/sse/streamable-http)
├── resources/          ← Docs, templates, prebuilt crews
├── tools/              ← 15 tools + shared utils.py
├── prompts/            ← Guided workflows (design_crew, debug_crew)
└── knowledge/          ← ChromaDB indexer + retriever

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📖 Documentación en Español

La documentación de CrewAI está disponible en inglés en docs.crewai.com. Para usar el MCP en español:

• El motor RAG indexa docs en inglés pero responde preguntas en cualquier idioma
• Los templates de crews aceptan descripciones de proyecto en español
• Las herramientas retornan mensajes en inglés; el LLM que consume el MCP traduce al contexto del usuario

Guías rápidas en español:

Guía	Descripción
Instalación y setup	Clonar, instalar dependencias, conectar a tu IDE
CyberOps template	Equipo de 5 agentes para crear MVPs desde cero
Herramientas	Referencia completa de las 15 herramientas
Ejemplo: crear un proyecto	create_project + apply_template en 2 pasos

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📝 License

MIT