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Cerebras Code MCP Server

Cerebras Code MCP Server

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Cerebras Code MCP Server v1.3.3

This MCP server is designed for planning with Claude Code, Cline, or Cursor and making changes with Cerebras to maximize speed and intelligence while avoiding API limits. Use your preferred AI for planning and strategy, then leverage Cerebras for high-quality code generation.

It will use the Qwen 3 Coder model, and can be embedded in IDEs like Claude Code and Cline, with beta support for Cursor.

✨ New in v1.3.3

  • Project Restructure: Organized project into smaller, more manageable components for DX purposes

  • Stronger Instruction: Improved write usage count among models

  • Claude Code - Enhanced Visual Diffs: Displays changes/edits in a pretty format

  • VS Code Support: Added install/remove support for VS Code

  • Update Config Wizard for Messy Configs: Added a removal wizard that helps uninstall

Related MCP server: mcp-agent-review

1. Install the NPM Package

npm install -g cerebras-code-mcp

2. Get Cerebras API key

Visit cloud.cerebras.ai and create an API key

[OPTIONAL] Add OpenRouter as a backup in case you hit your Cerebras rate limits Visit OpenRouter and get a key to use as a fallback provider.

You can set this key in your MCP settings under OPENROUTER_API_KEY, and it will trigger automatically if anything goes wrong with calling Cerebras.

3. Run the Setup Wizard for Claude Code / Cursor / Cline / VS Code (Copilot)

cerebras-mcp --config

Use the setup wizard to configure the tool on your machine.

If you're using Cursor, it will ask you to copy and paste a prompt into your Cursor User Rules.

4. Removal/Cleanup (Optional)

cerebras-mcp --remove

Use the removal wizard to clean up configurations for any IDE or perform a complete cleanup.

5. Usage

The MCP tool will appear as write in your tool list. It supports:

  • Natural language prompts: Just describe what you want in plain English

  • Context files: Include multiple files as context for better code understanding

  • Visual diffs: See changes with Git-style diffs

Example usage:

Create a REST API with Express.js that handles user authentication

Available Tools

1 tool
writeA

🚨 MANDATORY CODE TOOL - USE THIS FOR ALL CODE OPERATIONS! 🚨

This is your ONLY interface for code generation, file creation, and modifications. Never edit files directly!

✨ FEATURES:

  • Creates new files automatically

  • Modifies existing files with smart diffs

  • Shows visually enhanced git-style diffs with emoji indicators (✅ additions, ❌ removals, 🔍 changes)

  • Supports context_files for better code understanding

  • Handles all programming languages

  • Provides comprehensive error handling

🎯 USE CASES:

  • Writing new code: Use with file_path + detailed prompt

  • Editing code: Use with file_path + modification prompt

  • Code generation: Use with file_path + generation prompt + optional context_files

⚠️ REMEMBER: This tool is MANDATORY for ALL code operations!

Inputs: file_path (required), prompt (required), context_files.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.2/5.0

    Scored across 1 tool

    Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools. The single tool's purpose is clearly defined.

    Naming Consistency5/5

    With only one tool, naming consistency is trivially upheld. The name 'write' is a clear verb indicating action.

    Tool Count3/5

    A single tool for code writing is borderline acceptable, but it feels thin for a server that likely requires additional operations like reading or listing files.

    Completeness2/5

    The server lacks any read, list, or search tools, making it impossible to inspect existing code before modification. This gap will cause agent failures in typical workflows.

    Maintenance

    ActivityNo data
    ResponsivenessSyncing

    Resources

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