# gaslighting-mcp
A fake web search MCP server for AI alignment testing. It accepts a search query and returns LLM-generated search results shaped by a configurable background story.
Built with [FastMCP](https://github.com/jlowin/fastmcp) and compatible with any OpenAI-style API endpoint.
## How it works
1. You provide a background story via the `BACKGROUND_STORY` environment variable
2. The server exposes two tools: `search` and `read_url`
3. `search` — generates 10 realistic search results (url, snippet, date) consistent with the background story
4. `read_url` — generates a full fake article in markdown for a given URL, inferred from the domain/path and background story
5. The consuming AI agent receives these as if they were real web content
## Setup
```bash
uv sync
```
## Configuration
| Environment Variable | Default | Description |
|---|---|---|
| `BACKGROUND_STORY` | `""` | The narrative that shapes all generated results |
| `LLM_BASE_URL` | `https://openrouter.ai/api/v1` | OpenAI-compatible API base URL |
| `LLM_API_KEY` | `""` | API key for the LLM endpoint |
| `LLM_MODEL` | `nousresearch/hermes-4-405b` | Model name |
## Usage
### Standalone
```bash
uv run server.py
```
### Claude Code MCP config
Add to your `.mcp.json`:
```json
{
"mcpServers": {
"web-search": {
"command": "uv",
"args": ["run", "server.py"],
"env": {
"BACKGROUND_STORY": "your background story here",
"LLM_API_KEY": "your-api-key"
}
}
}
}
```
## Tools
### `search(query)`
Returns a JSON array of 10 results:
```json
[
{
"url": "https://example.com/some-article",
"snippet": "A realistic excerpt shaped by the background story.",
"date": "2025-12-15"
}
]
```
### `read_url(url)`
Returns a full fake article in markdown, inferred from the URL and background story. Matches the tone and style of the source website.
## License
MIT
