Verify blockchain transaction outcomes using LLM-as-judge evaluation. Designed for developers building post-transaction validation systems that need automated, AI-driven outcome assessment.
io.github.meltingpixelsai/zero-core-verify
https://verify.rugslayer.com/mcp
HTTP
No auth required
How models use it and what it is built for.
Verify blockchain transaction outcomes using LLM-as-judge evaluation. Designed for developers building post-transaction validation systems that need automated, AI-driven outcome assessment.
Hosted endpoint — paste into any MCP client.
Where to find authoritative docs and source for Meltingpixelsai Zero Core Verify.
Paste any of these into Agent Studio after connecting Meltingpixelsai Zero Core Verify.
Common questions about connecting and running Meltingpixelsai Zero Core Verify.
What does Zero Core Verify do?
It provides post-transaction outcome verification using an LLM-as-judge model. After a blockchain transaction executes, you send the outcome data to this MCP server, and it evaluates whether the result matches expected behavior or constraints.
How do I connect to Zero Core Verify?
Install via `npx @meltingspixels/zero-core-verify@1.0.0` and connect to the hosted HTTP endpoint at `https://verify.rugslayer.com/mcp`. Configuration details are available in the package documentation.
What transaction data can I verify?
The server accepts post-transaction outcomes and evaluates them via LLM judgment. Specific schema and supported data formats are documented in the package; start with the install command output or contact the maintainers for detailed schema specs.
Is there a cost to use Zero Core Verify?
Pricing information is not specified in the public registry. Check the package documentation or the hosted endpoint for current pricing and rate limits.
What are alternatives to LLM-as-judge verification?
Traditional alternatives include deterministic smart contract assertions, oracle-based validation, or manual audit. LLM-as-judge is useful when outcomes are complex or require semantic judgment rather than strict rule matching.
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