Dev Team MCP
Autonomous AI software development pipeline that transforms tickets into production-ready code through planning, coding, testing, reviewing, and delivery stages.
README
Dev Team MCP — Autonomous AI Software Development Team
Submit a ticket → get production-ready code.
An autonomous MCP server that runs a full software development pipeline: Planner → Coder → Tester → Reviewer → Delivery
Runs on port 8002 alongside:
- DevOps MCP (
:8000) — Docker, K8s, AWS, Git- Dev Agent MCP (
:8001) — Code generation in 18 languages
Architecture
┌─────────────────────────────────────────────────────────────────────┐
│ Claude Code / Copilot Chat │
│ │
│ MCP Stdio Adapters: │
│ ├── devops → mcp-server :8000 (DevOps — infra/git) │
│ ├── dev → mcp-dev-agent :8001 (Code gen — 18 languages) │
│ └── devteam → dev-team-mcp :8002 (Dev Team — full pipeline) │
│ │ │
│ ┌─────────▼─────────┐ │
│ │ ORCHESTRATOR │ │
│ └─────────┬─────────┘ │
│ │ │
│ ┌─────────────────┼─────────────────┐ │
│ ▼ ▼ ▼ ▼ │
│ PLANNER CODER TESTER REVIEWER │
│ Decompose Generate Write & Security + │
│ ticket into production run tests perf + style │
│ plan + stack code files fix failures checklist │
│ │ │ │ │ │
│ └─────────────────┴─────────────────┴─────────────────┘ │
│ │ │
│ ┌─────────▼─────────┐ │
│ │ DELIVERY.md │ │
│ │ git repo + tag │ │
│ └───────────────────┘ │
└─────────────────────────────────────────────────────────────────────┘
Each agent uses:
- LLM (Ollama / OpenAI / Anthropic) for reasoning
- Dev Agent :8001 for high-quality code generation and reviews
- DevOps MCP :8000 for git operations and deployments
Quick Start
1. Install
cd ~/dev-team-mcp
make install
2. Configure
cp .env.example .env
# Edit .env — choose LLM_PROVIDER (default: ollama)
3. Run
# Start this server
make dev # Dev server on :8002 with auto-reload
# Or start all three MCP servers at once
make start-all
4. Verify
curl http://localhost:8002/health | jq
How to Use
Submit a ticket (async)
curl -X POST http://localhost:8002/ticket \
-H "Content-Type: application/json" \
-d '{
"title": "Add JWT authentication to FastAPI app",
"description": "Add JWT-based auth with login endpoint, token refresh, and protected routes. Use python-jose.",
"language": "python",
"framework": "fastapi",
"priority": "high",
"labels": ["feature", "security"]
}'
Response:
{
"ticket_id": "a1b2c3d4e5f6",
"status": "pending",
"message": "Ticket accepted. Pipeline started: Planner -> Coder -> Tester -> Reviewer. Poll GET /ticket/a1b2c3d4e5f6 for status."
}
Poll for status
curl http://localhost:8002/ticket/a1b2c3d4e5f6 | jq
{
"ticket_id": "a1b2c3d4e5f6",
"status": "done",
"output_path": "/home/user/dev-team-mcp/workspace/add-jwt-auth-a1b2c3d4e5f6",
"review_score": 88,
"plan_summary": "Implement JWT authentication..."
}
Get all generated files
curl http://localhost:8002/ticket/a1b2c3d4e5f6/artifacts | jq
Get a specific file
curl http://localhost:8002/ticket/a1b2c3d4e5f6/artifacts/auth/jwt.py | jq .content
Blocking / sync mode (for small tasks)
curl -X POST http://localhost:8002/ticket/sync \
-H "Content-Type: application/json" \
-d '{"title": "Hello world script", "description": "Python script that prints hello world and current time"}'
MCP Tools (for Claude Code)
Once registered in ~/.claude/settings.json, you can use these tools directly in Claude:
| Tool | Description |
|---|---|
devteam_submit_ticket |
Submit a ticket for autonomous development |
devteam_submit_sync |
Submit and wait (blocking) |
devteam_ticket_status |
Check pipeline progress |
devteam_ticket_logs |
Stream agent log entries |
devteam_list_tickets |
List all tickets |
devteam_list_artifacts |
List generated files |
devteam_get_artifact |
Get a specific file content |
devteam_review_report |
Get code review score + checklist |
devteam_cancel_ticket |
Cancel a ticket |
devteam_health |
Health check |
Pipeline Stages
1. Planner Agent
- Reads the ticket and produces a structured JSON plan
- Chooses the minimal viable tech stack
- Breaks work into numbered steps with file targets
- Flags security concerns (OWASP Top-10)
- Defines test strategy and CI/CD approach
2. Coder Agent
- Generates production-ready code for every file in the plan
- Uses Dev Agent :8001 when available (falls back to direct LLM)
- Applies OWASP mitigations (input validation, parameterised queries, no hardcoded secrets)
- Auto-retries with alternative approach on failure
3. Tester Agent
- Generates unit + integration tests for every source file
- Runs tests via the language's native test runner
- On failure: asks LLM to fix the implementation and re-runs (loop)
- Tracks coverage percentage
4. Reviewer Agent
- Full security audit (uses Dev Agent :8001 + LLM bundle review)
- Performance analysis
- Documentation completeness check
- Production readiness checklist (12 criteria)
- Auto-fixes medium/low issues
- Approves (score ≥ 75) or rejects with detailed feedback
Delivery
- All files written to
workspace/<slug>-<ticket_id>/ - Git repository initialised with commit history
DELIVERY.md— full handover documentproduction-ready-<id>git tag applied when approved
Output Structure
workspace/add-jwt-auth-a1b2c3d4e5f6/
├── DELIVERY.md ← Human-readable handover
├── auth/
│ ├── jwt.py ← JWT implementation
│ ├── routes.py ← Protected routes
│ └── test_jwt.py ← Unit tests
├── main.py ← FastAPI app
├── requirements.txt
└── .github/
└── workflows/
└── ci.yml ← GitHub Actions CI
Configuration
| Env var | Default | Description |
|---|---|---|
LLM_PROVIDER |
ollama |
ollama / openai / anthropic |
OLLAMA_MODEL |
mistral |
Any Ollama model (codestral, llama3.1, etc.) |
OPENAI_API_KEY |
— | Required when LLM_PROVIDER=openai |
ANTHROPIC_API_KEY |
— | Required when LLM_PROVIDER=anthropic |
DEVOPS_MCP_URL |
http://localhost:8000 |
DevOps MCP server URL |
DEV_AGENT_URL |
http://localhost:8001 |
Dev Agent MCP server URL |
DEV_TEAM_PORT |
8002 |
This server's port |
MAX_RETRIES |
3 |
Max LLM retries per step |
MAX_TEST_FAILURES |
5 |
Max test fix iterations |
WORKSPACE_DIR |
./workspace |
Where generated repos land |
Running Tests
make test
Full 3-Server Stack
# Terminal 1: DevOps MCP (infrastructure)
cd ~/mcp && make dev
# Terminal 2: Dev Agent MCP (code gen)
cd ~/mcp-dev-agent && make dev
# Terminal 3: Dev Team MCP (autonomous pipeline)
cd ~/dev-team-mcp && make dev
Or use the convenience target:
cd ~/dev-team-mcp && make start-all
Generated by Dev Team MCP — autonomous AI software development pipeline
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