Aurelius

A fact-checked research MCP server. Aurelius gives any MCP-capable app — Claude (Desktop / Code / claude.ai), Gemini CLI, Cursor, and (via a remote deployment) ChatGPT — a set of research tools that verify every citation and claim against live web sources before presenting it. No more hallucinated papers.

Aurelius grew out of a multi-agent research framework and distills its best idea into a portable tool server: screen a topic → draft → fact-check → revise.

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Why this design solves the "API cost" problem

By default Aurelius runs in host-driven mode: the app you connect it to (Claude, Gemini, etc.) uses its own model to reason and write, and Aurelius just supplies the research and fact-checking tools. That means Aurelius needs no LLM API key of its own — the tokens are covered by your existing Claude/Gemini/ChatGPT subscription. The only optional key is Tavily for web search (free tier available).

There's also an optional autonomous mode (autonomous_research / aurelius-research) where Aurelius drives its own LLM — that one needs an LLM API key with quota.

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Install

pip install aurelius-mcp

The bare name aurelius was already taken on PyPI, so the package ships as aurelius-mcp. The import name (import aurelius) and the CLI command (aurelius) are unchanged.

This provides two commands:

• aurelius — launch the MCP server (stdio). This is what MCP clients run.
• aurelius-research "<topic>" — run one autonomous research job from the terminal.

If aurelius isn't found (the pip scripts dir may not be on your PATH — common on Windows), use the equivalent module form anywhere a command is expected: "command": "python", "args": ["-m", "aurelius"].

Get a Tavily key (for web search / verification)

Create a free key at https://tavily.com and expose it as TAVILY_API_KEY (see the config snippets below, which inject it into the server's environment).

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Connect it to your app (local / stdio)

Claude Desktop

Edit claude_desktop_config.json (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "aurelius": {
      "command": "aurelius",
      "env": { "TAVILY_API_KEY": "tvly-your-key" }
    }
  }
}

Restart Claude Desktop. See examples/claude_desktop_config.json.

Claude Code

claude mcp add aurelius --env TAVILY_API_KEY=tvly-your-key -- aurelius

Cursor

Add to ~/.cursor/mcp.json (or the project .cursor/mcp.json):

{
  "mcpServers": {
    "aurelius": { "command": "aurelius", "env": { "TAVILY_API_KEY": "tvly-your-key" } }
  }
}

Gemini CLI

Add to ~/.gemini/settings.json:

{
  "mcpServers": {
    "aurelius": { "command": "aurelius", "env": { "TAVILY_API_KEY": "tvly-your-key" } }
  }
}

Then just ask: "Use Aurelius to research the historical correlation between GDP growth and unemployment, and verify every citation."

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Tools

Tool	What it does	Needs
screen_topic(topic)	Screen a topic against the restricted-domain policy	—
get_research_policy()	Return the accept/reject policy	—
draft_outline(topic)	Standard academic outline scaffold	—
web_search(query, …)	Search the web for evidence	Tavily key
verify_citation(citation)	Check a citation exists in reputable sources	Tavily key
save_draft(content)	Save the Markdown draft	—
save_report(content)	Save the verification report	—
autonomous_research(topic, model, …)	Run the whole loop itself	LLM key

Outputs are written to ./aurelius_output/ (override with AURELIUS_OUTPUT_DIR).

The Claude skill

skill/aurelius/SKILL.md teaches a host model the exact screen → draft → verify → save workflow. Drop it into your Claude Code/Agent skills so the model uses the tools rigorously.

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Autonomous mode (optional, needs an LLM key)

export OPENAI_API_KEY=sk-...          # or ANTHROPIC_API_KEY / GOOGLE_API_KEY
export TAVILY_API_KEY=tvly-...
aurelius-research "Health effects of microplastics in drinking water" --model gpt-4o-mini-2024-07-18 --rounds 2

Provider is auto-detected from the model name (gpt-* → OpenAI, claude-* → Anthropic, gemini-* → Google).

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Platform support (honest status)

Platform	Status
Claude Desktop / Code	✅ Local stdio
Gemini CLI, Cursor	✅ Local stdio
ChatGPT	⚠️ Needs a remote (HTTP/SSE) deployment — on the roadmap
Perplexity	❌ No user-added MCP servers yet

License

MIT