[AISTATS2021] Official implementation of "Sample Elicitation"
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Updated
Apr 12, 2021 - Python
[AISTATS2021] Official implementation of "Sample Elicitation"
Running UK AISI's Inspect in the Cloud
MCP as a Judge is a behavioral MCP that strengthens AI coding assistants by requiring explicit LLM evaluations
Course-ready CLI reference for the Model Context Protocol. Demonstrates all six MCP primitives (tools, resources, prompts, sampling, elicitation, roots) wired to Anthropic's Claude. Adapted from Anthropic Academy for O'Reilly Live Training.
REST bridge to the MCP ecosystem, powered by mcp-use
Enhanced FastMCP server with real-time progress reporting, Pydantic elicitation, context logging & Claude Sonnet 4.5 integration — file operations with BASE_DIR security
Let existing MCP servers ask for missing required tool arguments through MCP elicitation, without changing the upstream server.
MCP server for conversational meal planning with OAuth 2.1 auth, multi-step elicitation, LLM sampling, and background tasks. Built with FastMCP, deployed to GKE.
Transparent MCP proxy that gates destructive tool calls behind human approval — elicitation, webhooks, WhatsApp. Drop-in for any MCP server.
A meeting becomes a scope tree a build can run against. Agent skills for Claude Code and Codex.
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