Provides an enterprise-grade MCP server that orchestrates AI-powered code analysis, migration, testing, and optimization inside IDEs.
Configuration
View docs{
"mcpServers": {
"iamnishant51-atlas-mcp-server": {
"command": "npx",
"args": [
"-y",
"atlas-pipeline-mcp"
],
"env": {
"OPENAI_API_KEY": "YOUR_API_KEY",
"OLLAMA_BASE_URL": "http://localhost:11434",
"ANTHROPIC_API_KEY": "YOUR_API_KEY"
}
}
}
}Atlas MCP Server provides an enterprise-grade machine-assisted code pipeline that integrates with your IDE to enable intelligent analysis, migration, testing, and optimization of code. It orchestrates intent, context, decomposition, variants, critique, and optimization to help you design, refactor, and validate code more effectively inside your development environment.
You use Atlas MCP Server by connecting your MCP client (such as an IDE plugin or built-in assistant) to the server. The system automatically activates the most relevant tool based on your request and guides you through a task-oriented workflow, from understanding intent to delivering optimized code.
Follow these concrete steps to install and start using Atlas MCP Server in your development environment.
# Step 1: Install Atlas MCP Server globally
npm install -g atlas-pipeline-mcp
# Step 2: Run the automatic IDE setup
atlas-mcp-setup
# Step 3: Restart your IDE to connect to the Atlas MCP ServerIf you prefer running models locally or want to supply your own API keys, configure Atlas to use a local setup. The following example shows how to specify the run command and environment keys.
{
"atlas": {
"command": "npx",
"args": ["-y", "atlas-pipeline-mcp"],
"env": {
"OLLAMA_BASE_URL": "http://localhost:11434",
"OPENAI_API_KEY": "sk-...",
"ANTHROPIC_API_KEY": "sk-..."
}
}
}Predictive bug detection that analyzes code patterns, complexity metrics, and historical data to forecast issues with 70-85% accuracy.
Context-aware code suggestions with pattern detection, best practice enforcement, and intelligent auto-completion.
Large-scale refactoring with dependency-aware modifications and impact analysis for safe transformations.
Natural language code search that finds code by intent rather than keywords.
Intelligent Git conflict resolution using code analysis and context understanding to suggest optimal merge strategies.
Tech debt quantification and tracking with actionable metrics and remediation roadmaps.
Frontend performance analysis and guidance to fix rendering and resource bottlenecks.
CSS architecture analysis with design token generation and conversions between CSS systems.
Professional animation generator for CSS, Framer Motion, GSAP, and related timelines with accessibility support.
API integration helper that generates types, hooks, mocks, validation schemas, and clients.
Full agentic pipeline implementing Intent → Context → Decompose → Variants → Critique → Optimize.
Intent analysis that extracts actionable goals from natural language requests.
Project context gathering including structure, dependencies, and file relationships.
Git history analysis covering commits, branches, and file evolution.
Task decomposition into a directed acyclic graph of subtasks.
Generate multiple implementation variants with pros/cons analysis.
Automated code review with quality scores and security checks.
Deep critique for quality, security, performance, and maintainability.
Code optimization driven by critique feedback and best practices.
Smart refactoring with complexity metrics and structural analysis.
Security scanner with CWE IDs and OWASP mappings.
Architectural guidance from a 15+ year veteran perspective.
In-depth performance optimization and Web Vitals improvements.
Enterprise-grade vulnerability detection with compliance assessment.
State management pattern comparison and scalability analysis.
API design review templates and best practices.
UI/UX design inspiration and production-ready code across frameworks.
Frontend performance diagnostics and targeted fixes.
CSS architecture analysis and token generation with unused styles detection.
Animation code generation with multiple libraries and accessibility.
Frontend API integration helpers including hooks and mocks.
Performance profiling and time/memory complexity analysis.
Test case generation for Jest, Vitest, Pytest, Mocha.
Auto-generation of documentation in JSDoc, TSDoc, or PyDoc.
Dependency analysis and vulnerability scanning.
Real-time metrics dashboards for project health.
Code explanation with complexity analysis and pattern detection.
Smart debugging with root cause analysis and fix suggestions.
Advanced sequential reasoning for complex problem solving.
Provider status checks for LLM backends.