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Cerebras

Cerebras Code MCP Server

Official
by Cerebras

write

Generate or modify code files with smart diffs. Provide file path and detailed prompt to create or edit files using context for accurate code generation.

Instructions

🚨 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!

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesREQUIRED: Absolute path to the file (e.g., '/Users/username/project/file.py'). This tool will create or modify the file at this location.
promptYesREQUIRED: A comprehensive plan dump that MUST include: 1) EXACT method signatures and parameters, 2) SPECIFIC database queries/SQL if needed, 3) DETAILED error handling requirements, 4) PRECISE integration points with context files, 5) EXACT constructor parameters and data flow, 6) SPECIFIC return types and data structures. Be extremely detailed - this is your blueprint for implementation.
context_filesNoOPTIONAL: Array of file paths to include as context for the model. These files will be read and their content included to help understand the codebase structure and patterns.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description explains features like creating files, modifying with smart diffs, and supporting context files. It lacks details on destructiveness or error handling specifics, but covers key behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long and uses excessive formatting (emojis, all caps). While structured clearly, it contains redundant emphasis and could be more concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers many aspects but misses details about output/return values. Given no output schema, this is a gap. It also lacks information on failure modes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds valuable context, especially for the 'prompt' parameter with detailed instructions on what to include. This goes beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is for code operations, including creation, modification, and generation. It emphasizes being the only interface for such tasks, distinguishing itself effectively.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit use cases and scenarios, such as writing new code or editing existing files. It also includes a warning not to edit files directly, offering clear guidance on when to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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