🔗 FactAnchor-MCP

Reduce AI Hallucinations by ~80% using Local Context Anchoring.

FactAnchor-MCP is a zero-cost, fully local Model Context Protocol server that grounds your AI assistant (Claude Desktop, Cursor, VS Code, Claude Code) in real, fetched web text — and forces it to answer only from that text.

• 💸 ₹0 Hosting Cost — runs entirely on your machine. No cloud, no paid API keys.
• 🛡️ Strict Guardrails — the LLM must cite sources or say "I cannot find a verified source for this information."
• 🔎 Free Web Fetching — uses DuckDuckGo's free search + page scraping (no Serper/Google keys).
• ⚡ Zero-config setup — pip install -e . + connect your MCP client. Browser auto-installs on first start.

⭐ If FactAnchor-MCP helps you ship more reliable, hallucination-free AI, please consider starring the repository. It takes one click and helps more developers discover a truly zero-cost way to ground their agents. Thank you! 🙏

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🚀 1-Minute Quick Start

Option A — Recommended (cross-platform, no path editing)

git clone https://github.com/Tausifonly001/FactAnchor-MCP.git
cd FactAnchor-MCP
pip install -e .          # installs the `factanchor-mcp` command

Then add this to your claude_desktop_config.json (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "FactAnchor-MCP": {
      "command": "factanchor-mcp"
    }
  }
}

Option B — Simple (use the script path directly)

git clone https://github.com/Tausifonly001/FactAnchor-MCP.git
cd FactAnchor-MCP
pip install -r requirements.txt

Add the absolute path to server.py:

{
  "mcpServers": {
    "FactAnchor-MCP": {
      "command": "python",
      "args": ["/absolute/path/to/FactAnchor-MCP/server.py"]
    }
  }
}

<details> <summary>📂 Per-OS path examples</summary>

• Windows: "C:\\Users\\you\\FactAnchor-MCP\\server.py"
• macOS / Linux: "/Users/you/FactAnchor-MCP/server.py" or "/home/you/FactAnchor-MCP/server.py"

</details>

3. Restart your client

You'll now see the fetch_verified_context tool available. Ask a factual question and watch the assistant ground its answer in live, cited sources.

✅ Zero-config: on first launch, FactAnchor silently installs the Playwright Chromium browser in the background. No crawl4ai-setup or manual browser commands required.

💡 Want uv instead of pip? uv pip install -e . works identically, and the factanchor-mcp command lands on your PATH.

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🧩 Supported Clients (drop-in configs)

FactAnchor-MCP is a standard MCP server, so it works with any MCP-compatible client. Below are ready-to-paste configs. Every client uses the same two shapes:

• Option A (recommended): "command": "factanchor-mcp" — needs pip install -e . (so the command is on your PATH).
• Option B (path-based): "command": "python" + "args": ["/abs/path/server.py"] — use this if the factanchor-mcp command isn't found.

<details open> <summary>💬 Claude Desktop</summary>

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

{
  "mcpServers": {
    "FactAnchor-MCP": { "command": "factanchor-mcp" }
  }
}

Restart Claude Desktop. Tool appears in the tools list.

</details>

<details open> <summary>🖥️ opencode</summary>

File: .opencode.jsonc (project root)

{
  "mcpServers": {
    "FactAnchor-MCP": { "command": "factanchor-mcp" }
  }
}

Verify with /mcp — fetch_verified_context should be listed.

</details>

<details open> <summary>⌨️ Claude Code / Kimi Code / Qwen Code / Cline / Roo Code</summary>

These are Claude-Code-style clients. Use a project .mcp.json:

{
  "mcpServers": {
    "FactAnchor-MCP": { "command": "factanchor-mcp" }
  }
}

Or add it from the CLI (runs the same server):

claude mcp add factanchor -- factanchor-mcp
# Kimi/Qwen/Cline equivalents use the same `mcp add` subcommand

</details>

<details open> <summary>🌀 Cursor</summary>

File: ~/.cursor/mcp.json (global) or .cursor/mcp.json (project)

{
  "mcpServers": {
    "FactAnchor-MCP": { "command": "factanchor-mcp" }
  }
}

Enable it in Settings → MCP and restart Cursor.

</details>

<details open> <summary>📝 VS Code (Copilot / MCP extension)</summary>

File: .vscode/mcp.json (note: VS Code uses a "servers" key)

{
  "servers": {
    "FactAnchor-MCP": {
      "type": "stdio",
      "command": "factanchor-mcp"
    }
  }
}

Open the Command Palette → MCP: List Servers to confirm it's connected.

</details>

<details open> <summary>🌟 Gemini CLI / Antigravity (Google)</summary>

File: .gemini/settings.json

{
  "mcpServers": {
    "FactAnchor-MCP": { "command": "factanchor-mcp" }
  }
}

Or: gemini mcp add factanchor -- factanchor-mcp

</details>

<details open> <summary>🔧 Generic MCP client (path-based fallback)</summary>

If the factanchor-mcp command isn't on your PATH, use the absolute path to server.py on every client above:

{
  "mcpServers": {
    "FactAnchor-MCP": {
      "command": "python",
      "args": ["/absolute/path/to/FactAnchor-MCP/server.py"]
    }
  }
}

Per-OS path examples:

• Windows: "C:\\Users\\you\\FactAnchor-MCP\\server.py"
• macOS: "/Users/you/FactAnchor-MCP/server.py"
• Linux: "/home/you/FactAnchor-MCP/server.py"

</details>

---

🛠️ How It Works

[Claude Desktop / Cursor / VS Code]
       │ (Asks a factual query)
       ▼
[FactAnchor MCP Server] ───► [Free DuckDuckGo Search + Page Scrape] (Live Facts)
       │                                            │
       │ (Injects Strict Guardrail + Verified Text) │ (Returns Raw Text)
       ▼                                            ◀
[Assistant answers ONLY from verified context → ~0% Hallucination]

1. Context Fetcher — fetch_verified_context(query) runs a free DuckDuckGo search to discover URLs, then Crawl4AI scrapes them concurrently into clean, LLM-optimized Markdown (navbars, ads, and footers auto-stripped).
2. Guardrail Injection — the fetched text is wrapped in a strict directive (see guardrail.py):
   • Answer only from <verified_context>.
   • If unanswerable, reply exactly: "I cannot find a verified source for this information."
   • Cite every claim in brackets like [Source: ...].
   • Never fall back to pre-trained knowledge.
3. Local-Only — the server uses the stdio transport, so all processing stays on your machine.

---

📦 Project Structure

File	Purpose
server.py	The MCP server + fetch_verified_context tool (FastMCP).
crawl_worker.py	Headless-scrape worker (Crawl4AI) run in an isolated subprocess for robust MCP stdio.
guardrail.py	The strict fact-anchoring prompt template.
text_cleaner.py	Markdown cleaning + truncation for Crawl4AI output.
pyproject.toml	Packaging + factanchor-mcp console command.
requirements.txt	Dependencies (mcp, ddgs/duckduckgo_search, crawl4ai).
claude_desktop_config.example.json	Copy-paste config snippet.

---

🧰 Requirements

• Python 3.10+
• Internet access (for the free search/scrape)

🔧 Tool Reference

fetch_verified_context(query: str, max_results: int = 3) -> str

Param	Default	Notes
query	—	The factual topic or question to ground.
max_results	3	Sources to pull (clamped 1–5).

---

🐛 Troubleshooting

• command not found: factanchor-mcp → you used Option A but didn't pip install -e ., or your venv isn't on PATH. Use Option B (script path) instead.
• Pages return only short snippets (first run) → Chromium is still installing in the background. Wait ~1–2 minutes and retry; subsequent runs are instant.
• "Browser executable doesn't exist" on Linux → install OS deps once: sudo playwright install-deps chromium (or sudo apt install libnss3 libatk-bridge2.0-0 libdrm2 libxkbcommon0 libgbm1 libasound2).
• Rate-limit system note from the tool → DuckDuckGo is throttling free search. Wait a few minutes and retry. The server never crashes; it returns a clean system note for the LLM.
• Tool not appearing in client → restart the client fully after editing the config, and check its MCP/Developer panel for errors.

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📈 Virality Strategy

• Before vs After video (X/Twitter & LinkedIn): show the assistant hallucinating a fake npm feature, then enable FactAnchor-MCP and watch it correctly say "I cannot find a verified source for this information." Tag @AnthropicAI with #MCP and #AI.
• Open-source launch: submit to the official MCP servers list and awesome-mcp collections.

---

🤝 Contributing

See CONTRIBUTING.md. Keep it zero-cost and local-first.

📋 Success Metrics (v1.0)

• ✅ ~80% reduction in made-up facts during test queries.
• ✅ <3 min user setup time (clone → install → config).
• ✅ ₹0.00 server maintenance bill.

⚠️ FactAnchor reduces hallucination but does not eliminate it. Always verify critical claims against the cited sources.

📜 License

MIT © FactAnchor-MCP contributors.