cfn-cerebras-mcp
FAST code generation via mcp__cerebras-mcp__write tool using Z.ai glm-4.6. Use for rapid test generation, boilerplate creation, and bulk code tasks in main chat. Prompt must be SHORTER than output. Ideal for tests, CRUD, migrations, and repetitive patterns.
Best use case
cfn-cerebras-mcp is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
FAST code generation via mcp__cerebras-mcp__write tool using Z.ai glm-4.6. Use for rapid test generation, boilerplate creation, and bulk code tasks in main chat. Prompt must be SHORTER than output. Ideal for tests, CRUD, migrations, and repetitive patterns.
Teams using cfn-cerebras-mcp should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cfn-cerebras-mcp/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cfn-cerebras-mcp Compares
| Feature / Agent | cfn-cerebras-mcp | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
FAST code generation via mcp__cerebras-mcp__write tool using Z.ai glm-4.6. Use for rapid test generation, boilerplate creation, and bulk code tasks in main chat. Prompt must be SHORTER than output. Ideal for tests, CRUD, migrations, and repetitive patterns.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Cerebras MCP Code Generation
**FAST** code generation via `mcp__cerebras-mcp__write` tool using Z.ai glm-4.6 model.
## When to Use
Use for **rapid test and code generation** when speed matters more than nuance:
- ✅ **Test files** - unit tests, integration tests, test fixtures
- ✅ **Boilerplate** - CRUD endpoints, data models, components
- ✅ **Bulk creation** - multiple similar files quickly
- ✅ **Migrations** - database migrations, schema updates
- ❌ **NOT for** complex architecture, security code, nuanced logic
**Rule**: Prompt must be SHORTER than expected output (blueprint style).
## Usage
```
mcp__cerebras-mcp__write:
file_path: /absolute/path/to/file.ts
prompt: |
Function: validateEmail(email: string): boolean
Steps:
- Regex test /^[^@]+@[^@]+\.[^@]+$/
- Return boolean result
Imports: none
Errors: none
context_files:
- /path/to/related/file.ts
```
## Prompt Format (Blueprint Style)
```
File: /path/to/file.ts
Function: functionName(params): returnType
Steps:
- Step 1
- Step 2
Imports: import { X } from './y'
Errors: throw new Error("message")
```
## Rules
1. **Prompt < Output**: Blueprint must be shorter than generated code
2. **Always include context_files**: When code needs imports from existing files
3. **Absolute paths only**: Use full paths, not relative
4. **One file per call**: Generate/modify single file
## Bad vs Good
**Bad** (verbose):
```
I need you to create a function that validates email addresses.
The function should take an email string as input and return true
if valid or false if invalid...
```
**Good** (blueprint):
```
Function: validateEmail(email: string): boolean
- Regex: /^[^@]+@[^@]+\.[^@]+$/
- Return: true if match, false otherwise
## Known Issues
- ℹ️ **Documentation Only**: This skill describes the MCP tool that's available in the main chat interface
- ℹ️ **No Separate Implementation**: There is no separate script to invoke - the tool is used directly
- ℹ️ **Main Chat Only**: This MCP tool is only available in the main chat, not within spawned agents
```