AgentGround Cross-Check Verifier

by Arafel187

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

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Alternatives to AgentGround Cross-Check Verifier

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genpark-agent-hallucinationofficial
AI & Machine Learning Autonomous Agents RAG Systems
alphaparkinc
F
license
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quality
B
maintenance
Enables autonomous agents and MCP clients to decompose text into atomic claims and verify them against reference knowledge, detecting ungrounded claims, numerical contradictions, and hallucinated entities.
Updated 7 days ago (2026-09-29 09:55 UTC)
7
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genpark-agent-hallucination
RAG Systems AI & Machine Learning Autonomous Agents
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license
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quality
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maintenance
Enables AI agents and MCP clients to decompose text into atomic claims and cross-verify them against reference knowledge to flag ungrounded claims, numerical contradictions, and hallucinated entities. Runs deterministically with zero dependencies over JSON-RPC stdio, avoiding LLM round-trips for routine verification tasks.
Updated 7 days ago (2026-09-29 09:55 UTC)
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ai2human Onus
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richard7463
A
license
Not graded
quality
A
maintenance
Enables AI agents to verify claims against evidence through MCP tools, returning approved, rejected, or needs_review verdicts with replayable receipts.
Updated 12 days ago (2026-09-24 09:22 UTC)
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Recommend Agentic Trust Layerofficial
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recommend-dev
A
license
Not graded
quality
B
maintenance
Enables agents to verify claims with evidence-based truth scores and confidence levels by running a deterministic pipeline of evidence lanes and adversarial checks.
Updated a month ago (2026-08-31 13:01 UTC)
26
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genpark-agentic-hallucinationofficial
RAG Systems AI & Machine Learning
Alpha-Park
F
license
Not graded
quality
B
maintenance
Enables sentence-level factual grounding verification and hallucination detection for RAG outputs via a native MCP server, providing deterministic scoring and structured telemetry.
Updated 6 days ago (2026-09-30 09:30 UTC)
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Lenz MCP Serverofficial
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lenzhq
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license
Not graded
quality
A
maintenance
Fact-check claims against independent sources via a multi-model pipeline, providing verdicts and confidence levels from any MCP client.
Updated a day ago (2026-10-05 10:23 UTC)
Apache 2.0