Groundcheck — verification with no model in the loop

An MCP connector that checks whether a claim's grounding is real — the quote is actually on the page, the arXiv id resolves, the code prints what it's said to, the number is right — with no language model anywhere in the verification path. Works in any MCP host: Claude, Gemini, or another.

Why this, and why it's hard

Every "fact-check" built into an assistant today ultimately asks a second model whether the first one was right. That doesn't verify anything — it relocates the error, because the checker hallucinates too. The genuinely hard, under-attempted thing is verification grounded in reality rather than in another model's opinion. That's all this does, and it does only that.

Scope, stated honestly, because over-claiming would defeat the point. Groundcheck confirms that the evidence a claim rests on is real and says what it's quoted to say. It does not judge whether a claim is semantically true — "this quote is on the cited page" is checkable; "the page's argument is correct" is not, and no amount of pretending makes it so. Every tool returns one of three verdicts, and it says unverifiable rather than guess:

Related MCP server: math-logic-mcp

The tools

Every result is {status, method, evidence, detail} — evidence is the concrete thing found (the quote, the stdout, the matching line, the computed value), so a verdict is auditable, not a black box.

It caught a mistake in its own author's work

check_citation exists because fabricated-but-plausible arXiv ids kept slipping into research write-ups — an id that looks right and resolves to nothing. check_math exists because 3.7 × 1400 was written as 8880 in a hardware deck (it's 5180). check_repo is the generalisation of a profile-README claim-checker that verifies every quoted number against its source repo. Each tool is a failure that actually happened, turned into a check.

There's one honest wrinkle worth reporting: while testing, I assumed arXiv 2606.01992 was fabricated and expected refuted — the tool returned checked. The tool was right and I was wrong: it's a real June-2026 paper. The verifier did its job against my own bad assumption, which is the entire reason to ground verification in a source rather than a hunch.

Use it

pip install -e .          # or: pip install -r requirements.txt
python -m pytest tests/   # 18 tests, no network needed (mocked transport)

Claude / Claude Code — add to your MCP config:

{
  "mcpServers": {
    "groundcheck": { "command": "python", "args": ["-m", "src.groundcheck.server"] }
  }
}

Gemini CLI / any MCP host — same stdio server; point your host's MCP config at python -m src.groundcheck.server. MCP is the reason one connector serves both.

Security

check_code executes the code you give it in a subprocess. It uses list-form subprocess (no shell, so nothing to inject) and kills on timeout, but it is not sandboxed from the network or filesystem. Only pass code you would run yourself. The other four tools are read-only (HTTP GET, file read, arithmetic).

Limitations

• Grounding, not truth. By design — see Scope above.

• Quote matching is exact (whitespace-normalised). A paraphrase that means the same thing returns refuted, because "means the same" needs a judge and a judge is what this tool refuses to be. Match the literal text.

• JS-rendered pages. check_quote reads the served HTML; a quote injected by client-side JavaScript won't be found. It fails safe (refuted), never a false checked.

• arXiv/Crossref only for citations. Other registries aren't wired up yet.

License

MIT — see LICENSE.