PromptTuner MCP
# PromptTuner MCP
<img src="docs/logo.png" alt="PromptTuner MCP Logo" width="200">
[](https://www.npmjs.com/package/@j0hanz/prompt-tuner-mcp-server)
[](LICENSE)
[](https://nodejs.org/)
PromptTuner MCP is an MCP server that fixes and boosts prompts using OpenAI, Anthropic, or Google Gemini.
## What it does
1. Validates and trims input prompts (enforces `MAX_PROMPT_LENGTH`).
2. Wraps the prompt as JSON inside sentinel markers (sanitizing markers, bidi control chars, and null bytes).
3. Calls the selected provider.
4. Normalizes LLM output (strips code fences / labels if present).
5. Returns human-readable text plus machine-friendly `structuredContent`.
## Features
- Polish and refine a prompt for clarity and flow (`fix_prompt`).
- Boost and enhance a prompt for clarity and effectiveness (`boost_prompt`).
- Craft a reusable workflow prompt for complex tasks (`crafting_prompt`).
- Simple structured outputs.
- Retry logic with exponential backoff for transient provider failures.
## Quick Start
PromptTuner runs over stdio only. The `dev:http` and `start:http` scripts are compatibility aliases (no HTTP transport yet).
### Claude Desktop
Add to `claude_desktop_config.json`:
```json
{
"mcpServers": {
"prompttuner": {
"command": "npx",
"args": ["-y", "@j0hanz/prompt-tuner-mcp-server@latest"],
"env": {
"LLM_PROVIDER": "openai",
"OPENAI_API_KEY": "sk-..."
}
}
}
}
```
> Replace the API key and provider with your preferred LLM. Only configure the key for the active provider.
## Configuration
PromptTuner uses minimal configuration. Set the provider and API key, and you're ready to go.
| Variable | Default | Description |
| ------------------- | -------- | ----------------------------------------------------- |
| `LLM_PROVIDER` | `openai` | `openai`, `anthropic`, or `google`. |
| `OPENAI_API_KEY` | - | Required for all tools when `LLM_PROVIDER=openai`. |
| `ANTHROPIC_API_KEY` | - | Required for all tools when `LLM_PROVIDER=anthropic`. |
| `GOOGLE_API_KEY` | - | Required for all tools when `LLM_PROVIDER=google`. |
| `LLM_MODEL` | - | Override the default model. |
| `DEBUG` | `false` | Enable debug logging. |
All tools are LLM-backed and require an API key for the selected provider.
### Default Models
| Provider | Default Model |
| ----------- | ---------------------------- |
| `openai` | `gpt-4o` |
| `anthropic` | `claude-3-5-sonnet-20241022` |
| `google` | `gemini-2.0-flash-exp` |
## CLI Options
| Flag | Description |
| --------------------------- | ----------------------------------- |
| `-h, --help` | Show help text. |
| `-v, --version` | Print version. |
| `--debug / --no-debug` | Enable/disable debug logging. |
| `--llm-provider <provider>` | `openai`, `anthropic`, or `google`. |
| `--llm-model <name>` | Override the default model. |
## Tools
All tools accept plain text, Markdown, or XML prompts. Responses include `content` (human-readable) and `structuredContent` (machine-readable).
Inputs are strict: extra fields are rejected. For `fix_prompt`/`boost_prompt`, only the `prompt` field is accepted.
### fix_prompt
Polish and refine a prompt for clarity and flow while preserving intent and structure.
| Parameter | Type | Required | Notes |
| --------- | ------ | -------- | ----------------------------------------------- |
| `prompt` | string | Yes | Trimmed, length-checked; extra fields rejected. |
Returns: `ok`, `fixed`.
### boost_prompt
Refine and enhance a prompt for clarity and effectiveness.
| Parameter | Type | Required | Notes |
| --------- | ------ | -------- | ----------------------------------------------- |
| `prompt` | string | Yes | Trimmed, length-checked; extra fields rejected. |
Returns: `ok`, `boosted`.
### crafting_prompt
Generate a structured, reusable workflow prompt for complex tasks based on a raw request and a few settings.
| Parameter | Type | Required | Notes |
| ------------- | ------ | -------- | ------------------------------------------------------- |
| `request` | string | Yes | Trimmed, length-checked; strict input. |
| `constraints` | string | No | Hard requirements to enforce (bullet list recommended). |
| `mode` | string | No | `general`, `plan`, `review`, `troubleshoot`. |
| `approach` | string | No | `conservative`, `balanced`, `creative`. |
| `tone` | string | No | `direct`, `neutral`, `friendly`. |
| `verbosity` | string | No | `brief`, `normal`, `detailed`. |
Returns: `ok`, `prompt`, `settings`.
## Response Format
- `content`: array of content blocks. First block is JSON for `structuredContent`, second is a short human message (or `Error: ...`).
- `structuredContent`: machine-parseable results.
- Errors return `structuredContent.ok=false` and an `error` object with `code`, `message`, optional `context` (sanitized, up to 200 chars), `details`, and `recoveryHint`.
- Error responses also include `isError: true`.
## Development
### Prerequisites
- Node.js >= 22.0.0
- npm
### Scripts
| Command | Description |
| ------------------------ | ----------------------------------------------------- |
| `npm run build` | Compile TypeScript and set permissions. |
| `npm run prepare` | Build on install (publishing helper). |
| `npm run dev` | Run from source in watch mode. |
| `npm run dev:http` | Alias of `npm run dev` (no HTTP transport yet). |
| `npm run watch` | TypeScript compiler in watch mode. |
| `npm run start` | Run the compiled server from `dist/`. |
| `npm run start:http` | Alias of `npm run start` (no HTTP transport yet). |
| `npm run test` | Run `node:test` once. |
| `npm run test:coverage` | Run `node:test` with experimental coverage. |
| `npm run test:watch` | Run `node:test` in watch mode. |
| `npm run lint` | Run ESLint. |
| `npm run format` | Run Prettier. |
| `npm run type-check` | TypeScript type checking. |
| `npm run inspector` | Run MCP Inspector against `dist/index.js`. |
| `npm run inspector:http` | Alias of `npm run inspector` (no HTTP transport yet). |
| `npm run duplication` | Run jscpd duplication report. |
| `npm run prepublishOnly` | Lint, type-check, and build before publish. |
## Project Structure
```text
src/
index.ts Entry point
cli.ts CLI parsing, logging bootstrap, shutdown handling
server.ts MCP server setup (stdio transport)
tools.ts Tool implementations
schemas.ts Zod input/output schemas
config.ts Configuration and constants
types.ts Shared types and error codes
lib/ Shared utilities (LLM, retry, telemetry, prompt utils)
tests/ node:test suites
dist/ Compiled output (generated)
docs/ Static assets
```
## Security
- API keys are supplied only via environment variables.
- Inputs are validated with Zod and additional length checks.
- Error context is included in debug mode (sanitized and truncated to 200 chars).
- Google safety filters are always enabled.
## Contributing
Pull requests are welcome. Please include a short summary, tests run, and note any configuration changes.
## License
MIT License. See `LICENSE` for details.
TDQS
Scored across 3 tools
The three tools have overlapping purposes in prompt improvement, with 'boost_prompt' and 'fix_prompt' both focusing on clarity and effectiveness, which could cause confusion. However, 'crafting_prompt' is more distinct as it generates structured workflows, providing some differentiation.
All tool names follow a consistent verb_noun pattern with clear, descriptive verbs ('boost', 'crafting', 'fix') and the same noun ('prompt'), making them predictable and easy to understand.
With only 3 tools, the server feels thin for a domain like prompt tuning, which might involve more operations such as evaluating prompts, testing variations, or managing prompt libraries. This limited set could restrict agent capabilities.
The toolset is incomplete for prompt tuning, missing essential operations like evaluating prompt effectiveness, comparing different versions, or storing/retrieving prompts. This creates gaps that could lead to agent failures in comprehensive prompt management tasks.