Every model has a knowledge cutoff; the world moved on. One call bridges the gap — latest versions, fresh CVEs, current state — so your agent stops answering from stale memory.
One keyless MCP call bridges the model's knowledge gap.
# Keyless over MCP — point any client at https://dynamicfeed.ai/mcp, then call:
whats_changed_since_your_training()
reality_check("The latest Python is 3.11")
{ "claim": "The latest Python is 3.11", "verdict": "outdated",
"current": "3.13.x", "source": "endoflife.date", "as_of": "2026-06-04" }
An LLM confidently states facts frozen at its training cutoff — last year's 'latest version', a patched-since CVE, a finished event. This is the bridge: call it before answering and the agent grounds itself in what's true now, with a citeable source.
It's targeted live ground-truth with provenance + freshness stamps — built for an agent to verify a claim and cite the source, not a page of blue links.
Yes, over MCP.