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MCP Tools - Multi-Server Architecture

A modular FastMCP server architecture providing development tools, analytics, and reporting for Claude Code integration.

πŸ—οΈ Architecture Overview

MCP Tools uses a multi-server composition architecture with three specialized servers:

  • 🎯 Coordinator (localhost:8002) - Main orchestration server that composes tools and reports

  • πŸ› οΈ Tools (localhost:8003) - Development workflow automation (PR analysis, code review, JIRA)

  • πŸ“ˆ Reports (localhost:8004) - Performance analytics and reporting (quarterly reports, metrics)

All servers can run independently or composed together through the coordinator using FastMCP's mount() pattern.

πŸš€ Quick Start

# Start all services ./scripts/start.sh # Check status ./scripts/status.sh # Stop all services ./scripts/stop.sh # Add to Claude Code (coordinator endpoint) claude mcp add mcp-tools http://localhost:8002/mcp/ --transport http --scope user

Development Setup

# Install dependencies poetry install # Run coordinator (mounts all servers) poetry run python coordinator/server.py # Or run individual servers poetry run python tools/server.py # Tools only (port 8003) poetry run python reports/server.py # Reports only (port 8004)

πŸ“Š Service Endpoints

Service

Port

Health Check

Purpose

Coordinator

8002

http://localhost:8002/health

Main composition server

Tools

8003

http://localhost:8003/health

Development workflows

Reports

8004

http://localhost:8004/health

Analytics & reporting

πŸ› οΈ Available Tools (14 Core Tools)

Development Workflow Tools (Tools Server)

1. PR Health (pr_health)

Analyzes PR health including open review threads, CI status, and merge readiness.

  • Input: GitHub PR URL, optional description

  • Output: Comprehensive health analysis with actionable solutions

  • Example: "pr_health https://github.com/owner/repo/pull/123"

2. Code Review (code_review)

Performs comprehensive code quality review with security and performance analysis.

  • Input: GitHub PR URL, optional focus area, max diff lines

  • Output: Structured code quality assessment

  • Example: "code_review https://github.com/owner/repo/pull/123 security"

3. Tech Design Review (tech_design_review)

Reviews technical design documents with architecture and implementation analysis.

  • Input: Document URL (Confluence/GitHub), optional focus area

  • Output: Design review with architecture recommendations

  • Example: "tech_design_review https://company.atlassian.net/wiki/pages/123456"

4. JIRA Transition (jira_transition)

Automates JIRA workflow transitions with intelligent state management.

  • Input: Ticket ID, target state (supports aliases: "dev", "review", "qa", "done")

  • Output: JIRA transition instructions with Atlassian MCP integration

  • Example: "jt SI-1234 start" or "jira_transition SI-1234 development"

5. Get JIRA Transitions (get_jira_transitions)

Calculates optimal transition paths between JIRA statuses.

  • Input: From status, optional to status

  • Output: Step-by-step transition path with MCP commands

  • Example: "get_jira_transitions 'Open' 'In Development'"

6. Epic Status Report (epic_status_report)

Generates comprehensive epic status with sub-task analysis and progress tracking.

  • Input: Epic ticket ID, optional focus area

  • Output: Epic progress analysis with assignee action items

  • Example: "epic_status_report SI-9038"

Analytics & Reporting Tools (Reports Server)

7. Quarterly Team Report (quarterly_team_report)

Generates comprehensive quarterly team performance reports with anonymized metrics.

  • Input: Team prefix, year, quarter, optional description

  • Output: Team analysis using JIRA and GitHub data

  • Example: "quarterly_team_report SI 2025 2"

8. Quarter-over-Quarter Analysis (quarter_over_quarter_analysis)

Analyzes team performance trends and size changes across multiple quarters.

  • Input: Team prefix, period (e.g., "2024", "2023-2025")

  • Output: Multi-quarter trend analysis with team composition tracking

  • Example: "quarter_over_quarter_analysis SI 2024"

9. Personal Quarterly Report (personal_quarterly_report)

Generates individual contributor performance reports for personal development.

  • Input: Team prefix, year, quarter

  • Output: Personal performance analysis with growth recommendations

  • Example: "personal_quarterly_report SI 2025 2"

10. Personal Quarter-over-Quarter (personal_quarter_over_quarter)

Analyzes personal performance trends and growth across multiple time periods.

  • Input: Team prefix, period

  • Output: Personal growth analysis with development insights

  • Example: "personal_quarter_over_quarter SI 2024"

System & Utility Tools

11. Setup Prerequisites (setup_prerequisites)

Validates and sets up all prerequisites required by MCP Tools.

  • Output: Comprehensive validation with setup instructions

  • Features: GitHub CLI, JIRA access, tool availability checks

12. Check Tool Requirements (check_tool_requirements)

Checks specific prerequisites for individual MCP tools.

  • Input: Tool name

  • Output: Tool-specific validation results

13. Echo (echo)

Simple connectivity test for MCP communication validation.

14. Get System Info (get_system_info)

System diagnostics and server health monitoring.

🐳 Container Architecture

Multi-Stage Dockerfiles

  • Builder Stage: Poetry dependency installation

  • Production Stage: Minimal runtime with non-root user

  • Multi-arch: Supports AMD64 and ARM64 architectures

Container Features

  • Health Checks: Built-in /health endpoints for all services

  • Security: Non-root user execution

  • Logging: Structured logging with configurable levels

  • Networking: Isolated bridge network for service communication

Docker Compose Services

services: mcp-coordinator: # Main orchestration (port 8002) mcp-tools: # Development tools (port 8003) mcp-reports: # Analytics server (port 8004)

πŸ”§ Development & Deployment

Environment Variables

Variable

Default

Description

MCP_SERVER_PORT

8002/8003/8004

Server port

LOG_LEVEL

INFO

Logging level

MOUNT_TOOLS

true

Mount tools server (coordinator only)

MOUNT_REPORTS

true

Mount reports server (coordinator only)

Container Management

# Build all containers podman-compose build # Start with logs podman-compose up # Background mode podman-compose up -d # Check status podman-compose ps # View logs podman-compose logs -f mcp-coordinator

🎯 Integration Patterns

Claude Code Integration

# Primary endpoint (coordinator with all tools) claude mcp add mcp-tools http://localhost:8002/mcp/ --transport http --scope user # Individual servers (if needed) claude mcp add mcp-tools-dev http://localhost:8003/mcp/ --transport http --scope user claude mcp add mcp-reports http://localhost:8004/mcp/ --transport http --scope user

Workflow Examples

# Complete development workflow claude "jt SI-1234 start -> pr_health https://github.com/owner/repo/pull/123 -> code_review same_url" # Quarterly reporting workflow claude "quarterly_team_report SI 2025 2 -> personal_quarterly_report SI 2025 2" # Epic management workflow claude "epic_status_report SI-9038 -> jt SI-1234 start -> create implementation plan"

🚨 Alpha Development Status

MCP Tools is currently in alpha development:

  • ⚠️ Not production ready - features and accuracy not guaranteed

  • πŸ”¬ Internal use only - data validation required

  • πŸ“Š Report outputs require manual verification

  • πŸ”„ Format and structure may change without notice

πŸ—οΈ Architecture Benefits

Modularity

  • Independent Deployment: Each server can run standalone

  • Specialized Concerns: Development tools vs. reporting separated

  • Scalable: Add new servers without modifying existing ones

FastMCP Composition

  • Server Mounting: Coordinator mounts specialized servers

  • Unified Interface: Single endpoint with all tools

  • Service Discovery: Automatic tool registration and health monitoring

Container-First Design

  • Production Ready: Multi-stage builds with security best practices

  • Orchestration: Docker Compose with networking and health checks

  • Portability: Runs consistently across development and production environments


Requirements: Python 3.11+, Poetry, Podman/Docker, Git, curl, jq

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security - not tested
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license - not found
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quality - not tested

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