# Before we start

## WedoLow MCP Server

WedoLow MCP Server connects beLow to your AI coding agents for intelligent, automated optimization. Guide code generation with real performance data.

### Core Capabilities

**Project-Aware Intelligence**

* Complete access to your project structure and dependencies
* Full visibility into compilation environment and build configuration
* Understanding of target platform and optimization constraints
* Context-driven AI optimization suggestions

**Iterative Optimization Loop**

* AI analyzes code and identifies optimization opportunities
* Real-time performance feedback and metrics gathering
* Automated application of optimizations
* Refinement based on measured results

### How It Works

**Setup** — Install MCP Server alongside beLow and configure your project

**Connect** — Link your AI agent (GitHub Copilot, Claude, Gemini, or other MCP-enabled LLM)

**Optimize** — Ask your AI agent to analyze and optimize your code

**Iterate** — AI refines optimizations based on performance metrics and your feedback

**Deploy** — Use optimized code in production

### Supported AI Platforms

* GitHub Copilot (VS Code & JetBrains) with GPT-4.1 and Claude Sonnet 4
* Claude (any MCP-enabled integration)
* Gemini CLI and Gemini Pro 2.5
* Junie (Beta) for JetBrains CLion
* Any MCP-enabled AI agent


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.wedolow.com/documentation/wedolow-mcp-server/before-we-start.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.