MCP Servers

gaslighting-mcp

A fake web search server that generates LLM-powered search results and full articles based on a configurable background story for AI alignment testing. It enables users to simulate a controlled web environment where AI agents interact with fabricated content tailored to a specific narrative.

README

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 and compatible with any OpenAI-style API endpoint.

How it works

You provide a background story via the BACKGROUND_STORY environment variable
The server exposes two tools: search and read_url
search — generates 10 realistic search results (url, snippet, date) consistent with the background story
read_url — generates a full fake article in markdown for a given URL, inferred from the domain/path and background story
The consuming AI agent receives these as if they were real web content

Setup

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

uv run server.py

Claude Code MCP config

Add to your .mcp.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:

[
  {
    "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

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