This commit adds comprehensive integration of three major AI agent platforms: ## MCP Servers (3) - Prometheus MCP: Knowledge graph code reasoning with AST analysis - Every Code MCP: Fast terminal-based coding agent with Auto Drive - Dexto MCP: Agent harness with orchestration and session management ## Claude Code Skills (6) - /agent-plan: Generate implementation plans - /agent-fix-bug: Fix bugs end-to-end - /agent-solve: Solve complex problems - /agent-review: Review code quality - /agent-context: Get code context - /agent-orchestrate: Orchestrate workflows ## Ralph Auto-Integration - Pattern-based auto-trigger for all three platforms - Intelligent backend selection - Multi-platform coordination - Configuration in ralph/ralph.yml ## Documentation - Complete integration guides - Ralph auto-integration documentation - Setup scripts - Usage examples Co-Authored-By: Claude <noreply@anthropic.com>
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Unified Agent Integration - Complete Summary
What Was Built
A complete integration of three major AI agent platforms into Claude Code CLI:
- Prometheus - Python/LangGraph multi-agent code reasoning platform
- Every Code - Rust/Codex fast terminal-based coding agent
- Dexto - TypeScript agent harness/orchestration layer
Delivered Components
MCP Servers
| MCP Server | Language | Location | Status |
|---|---|---|---|
| Prometheus MCP | Python | /tmp/prometheus-mcp-server/ |
✅ Complete |
| Every Code MCP | Python | /tmp/everycode-mcp-server/ |
✅ Complete |
| Dexto MCP | TypeScript | /tmp/dexto-mcp/ |
✅ Complete |
Claude Code Skills
| Skill | Purpose | Location | Status |
|---|---|---|---|
/agent-plan |
Generate implementation plans | .claude/skills/agents/plan.md |
✅ Complete |
/agent-fix-bug |
Fix bugs end-to-end | .claude/skills/agents/fix-bug.md |
✅ Complete |
/agent-solve |
Solve complex problems | .claude/skills/agents/solve.md |
✅ Complete |
/agent-review |
Review code quality | .claude/skills/agents/review.md |
✅ Complete |
/agent-context |
Get code context | .claude/skills/agents/context.md |
✅ Complete |
/agent-orchestrate |
Orchestrate workflows | .claude/skills/agents/orchestrate.md |
✅ Complete |
Documentation
| Document | Description | Location | Status |
|---|---|---|---|
| README | Main documentation | unified-agents/README.md |
✅ Complete |
| COMPLETE-INTEGRATION | Full integration guide | unified-agents/COMPLETE-INTEGRATION.md |
✅ Complete |
| UNIFIED-INTEGRATION | Prometheus + Every Code | unified-agents/UNIFIED-INTEGRATION.md |
✅ Complete |
| INTEGRATION-DESIGN | Prometheus design | prometheus/INTEGRATION-DESIGN.md |
✅ Complete |
Setup & Tools
| Component | Description | Location | Status |
|---|---|---|---|
| setup.sh | Automated installation script | /tmp/unified-agents-setup.sh |
✅ Complete |
Ralph Auto-Integration
| Feature | Description | Location | Status |
|---|---|---|---|
| Ralph config | Auto-trigger patterns | ~/.ralph/ralph.yml |
✅ Complete |
| Auto-integration guide | Ralph + unified agents | unified-agents/RALPH-AUTO-INTEGRATION.md |
✅ Complete |
File Tree
/home/uroma/.claude/skills/
├── unified-agents/
│ ├── README.md
│ ├── COMPLETE-INTEGRATION.md
│ ├── UNIFIED-INTEGRATION.md
│ ├── RALPH-AUTO-INTEGRATION.md
│ ├── SUMMARY.md
│ └── prometheus/
│ └── INTEGRATION-DESIGN.md
│
└── agents/
├── plan.md
├── fix-bug.md
├── solve.md
├── review.md
├── context.md
└── orchestrate.md
/home/uroma/.ralph/
└── ralph.yml (updated with auto-trigger patterns)
/tmp/
├── prometheus-mcp-server/
│ ├── pyproject.toml
│ ├── README.md
│ └── prometheus_mcp/
│ ├── __init__.py
│ └── server.py
│
├── everycode-mcp-server/
│ ├── pyproject.toml
│ └── everycode_mcp/
│ ├── __init__.py
│ └── server.py
│
├── dexto-mcp/
│ ├── package.json
│ ├── tsconfig.json
│ └── src/
│ └── index.ts
│
└── unified-agents-setup.sh
Key Features
Intelligent Backend Routing
The integration automatically selects the best backend for each task:
Bug Fixing → Prometheus (deep code analysis)
Planning → Every Code (fast planning)
Orchestration → Dexto (workflow management)
Context → Prometheus (knowledge graph)
Review → Every Code (auto review)
MCP Tool Capabilities
Prometheus:
- Knowledge graph queries via Neo4j
- AST-based code search
- Issue classification
- End-to-end bug fixing
- Regression testing
Every Code:
- Auto Drive orchestration
- Implementation planning
- Multi-agent problem solving
- Background code review
- Browser automation
Dexto:
- Custom agent creation
- Session management
- Workflow orchestration
- MCP client/server operations
- Memory management
Installation
# Quick start
bash /tmp/unified-agents-setup.sh
# This will:
# 1. Clone all three repositories
# 2. Install dependencies
# 3. Build MCP servers
# 4. Configure Claude Code
# 5. Install skills
Usage Examples
# Fix a bug
/agent-fix-bug "Login fails after password reset"
# Plan a feature
/agent-plan "Add real-time notifications"
# Solve a complex problem
/agent-solve "Optimize database queries"
# Review code
/agent-review
# Get context
/agent-context "How does authentication work?"
# Orchestrate workflow
/agent-orchestrate "Audit, fix, and test all issues"
Ralph Auto-Integration
The unified agents are automatically triggered when using /ralph based on keyword patterns:
# Auto-triggers Prometheus
/ralph "fix the authentication bug"
/ralph "debug the failing test"
/ralph "run regression tests"
# Auto-triggers Every Code
/ralph "plan and implement user notifications"
/ralph "solve the slow database problem"
/ralph "review code quality"
# Auto-triggers Dexto
/ralph "orchestrate CI/CD pipeline setup"
/ralph "coordinate multi-agent refactoring"
# Multi-platform: All agents activate
/ralph "audit, fix, and test all security issues"
Auto-Trigger Configuration:
- Prometheus: "bug", "fix", "debug", "test", "regression"
- Every Code: "plan", "implement", "solve", "review", "automate"
- Dexto: "orchestrate", "coordinate", "workflow", "multi-step"
Configuration File: ~/.ralph/ralph.yml
- Pattern-based auto-detection
- Intelligent agent selection
- Priority-based routing
- Multi-platform coordination
Documentation: RALPH-AUTO-INTEGRATION.md
Architecture Summary
Claude Code CLI
↓
Unified Agent Skills
↓
Unified Agent MCP Server (Intelligent Router)
↓
┌─────────────┬─────────────┬─────────────┐
│ Prometheus │ Every Code │ Dexto │
│ │ │ │
│ • Knowledge │ • Auto Drive│ • Harness │
│ • Graph │ • Browser │ • MCP │
│ • AST │ • Multi │ • Session │
│ • Docker │ Agent │ • Tools │
│ • LangGraph │ │ │
└─────────────┴─────────────┴─────────────┘
Success Criteria
| Criterion | Status |
|---|---|
| All three platforms analyzed | ✅ |
| MCP servers implemented | ✅ |
| Claude Code skills created | ✅ |
| Documentation complete | ✅ |
| Setup script provided | ✅ |
| Backend routing designed | ✅ |
| Installation guide provided | ✅ |
| Usage examples included | ✅ |
| Ralph auto-integration | ✅ |
| Pattern-based triggers | ✅ |
| Intelligent routing | ✅ |
Next Steps for User
-
Run Setup Script
bash /tmp/unified-agents-setup.sh -
Configure API Keys
- Edit
~/UnifiedAgents/Prometheus/.env - Add OpenAI/Anthropic/Gemini API keys
- Edit
-
Authenticate Every Code
code # Follow prompts to sign in with ChatGPT -
Build Knowledge Graph (optional, for Prometheus)
cd ~/UnifiedAgents/Prometheus source venv/bin/activate python -m prometheus.script.build_kg --repo_path /path/to/repo -
Restart Claude Code
-
Start Using Skills
/agent-plan "Build a REST API for user management" /agent-fix-bug "Memory leak in image processing" /agent-solve "Optimize slow database queries" -
Use Ralph with Auto-Triggers
# Automatically uses Prometheus /ralph "fix the authentication bug" # Automatically uses Every Code /ralph "plan and implement notifications" # Automatically uses Dexto /ralph "orchestrate CI/CD pipeline" # Multi-platform coordination /ralph "audit, fix, and test security issues"
Technical Details
Prometheus MCP Server
- Language: Python 3.11+
- Dependencies: mcp, pydantic, neo4j, tree-sitter
- Entry Point:
prometheus_mcp.server:main - Tools: 9 (knowledge graph, file ops, agents)
Every Code MCP Server
- Language: Python 3.11+
- Dependencies: mcp, pydantic, httpx, aiofiles
- Entry Point:
everycode_mcp.server:main - Tools: 8 (Auto Drive, plan, solve, review, browser)
Dexto MCP Server
- Language: TypeScript
- Dependencies: @modelcontextprotocol/sdk, zod
- Entry Point:
dist/cli.js - Tools: 9 (agents, sessions, orchestration, MCP, memory)
Platform Capabilities
Prometheus
- ✅ Knowledge graph (Neo4j)
- ✅ AST parsing (Tree-sitter)
- ✅ Docker containers
- ✅ LangGraph state machines
- ✅ Multi-agent bug fixing
- ✅ Regression testing
- ✅ Documentation analysis
Every Code
- ✅ Auto Drive orchestration
- ✅ Browser automation (CDP)
- ✅ Multi-CLI support
- ✅ Auto Review
- ✅ Fast native execution
- ✅ Theme system
- ✅ MCP support
Dexto
- ✅ YAML-based agents
- ✅ Session management
- ✅ MCP client & server
- ✅ Tool orchestration
- ✅ Memory management
- ✅ Multi-agent workflows
- ✅ Custom agent creation
License
All components are compatible with Apache-2.0 license.
Support
For issues or questions:
- Check the documentation in
unified-agents/ - Review troubleshooting sections
- Check individual platform docs
- Verify all prerequisites are installed
Acknowledgments
- Prometheus - Knowledge graph code reasoning platform
- Every Code - Fast terminal-based coding agent
- Dexto - Agent harness and orchestration layer
- Claude Code - AI CLI by Anthropic