com.pysolvr/llmprover
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Publisher-provided title
LLM Prover
Publisher-provided description
Evaluate agent workflows and LLMs on your own data: find wasted steps, pick models, catch drift.
Summary by lookupd
Lets an agent evaluate agent workflows and LLMs against custom datasets, flag wasted steps, compare models, and detect performance drift.
Install
Claude Code, remote (streamable-http)
claude mcp add --transport http llmprover https://mcp.llmprover.pysolvr.com/mcp
Codex, remote (streamable-http)
codex mcp add llmprover --url https://mcp.llmprover.pysolvr.com/mcp
Cursor, remote (streamable-http) → .cursor/mcp.json
{
"mcpServers": {
"llmprover": {
"url": "https://mcp.llmprover.pysolvr.com/mcp"
}
}
}Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.
Details
- Version: 1.0.0
- Transports: streamable-http
- Uptime (7 days): 100%
- First indexed:
- Last seen in registry:
- Website: https://llmprover.pysolvr.com
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