Provides integration with the Atlassian ecosystem to manage development workflows and documentation through Jira and Confluence.
Enables technical design reviews by analyzing document content and architectural recommendations hosted on Confluence.
Allows for comprehensive pull request health analysis, automated code quality reviews, and data extraction for team performance reports.
Automates Jira ticket transitions, generates epic status reports, and performs quarterly team performance analysis using Jira data.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Toolsanalyze the health of PR https://github.com/owner/repo/pull/123"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Tools - Multi-Server Architecture
A modular FastMCP server architecture providing development tools, analytics, and reporting for Claude Code integration.
ποΈ Architecture Overview
MCP Tools uses a multi-server composition architecture with three specialized servers:
π― Coordinator (
localhost:8002) - Main orchestration server that composes tools and reportsπ οΈ Tools (
localhost:8003) - Development workflow automation (PR analysis, code review, JIRA)π 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.
π Quick Start
Container-First Deployment (Recommended)
Development Setup
π Service Endpoints
Service | Port | Health Check | Purpose |
Coordinator | 8002 |
| Main composition server |
Tools | 8003 |
| Development workflows |
Reports | 8004 |
| Analytics & reporting |
π 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.
π³ 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
/healthendpoints for all servicesSecurity: Non-root user execution
Logging: Structured logging with configurable levels
Networking: Isolated bridge network for service communication
Docker Compose Services
π§ Development & Deployment
Environment Variables
Variable | Default | Description |
| 8002/8003/8004 | Server port |
| INFO | Logging level |
| true | Mount tools server (coordinator only) |
| true | Mount reports server (coordinator only) |
Container Management
π― Integration Patterns
Claude Code Integration
Workflow Examples
π¨ Alpha Development Status
MCP Tools is currently in alpha development:
β οΈ Not production ready - features and accuracy not guaranteed
π¬ Internal use only - data validation required
π Report outputs require manual verification
π Format and structure may change without notice
ποΈ 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