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"AI Footprints - Environmental and Digital Impact of Artificial Intelligence" matching MCP servers:

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    Provides comprehensive Swiss agricultural environmental compliance data covering water protection zones, ammonia emission limits, biodiversity requirements, and nutrient regulations from BAFU, BLW, and Agroscope. Enables AI assistants to search federal ordinances and verify farm compliance through specialized tools for GSchG, LRV, DZV, and other environmental laws.
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    Apache 2.0
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    Estimates the environmental footprint of your AI use — energy (kWh), miles driven, water used for cooling, and CO₂ — plus a prompt-efficiency score, working with any AI client by measuring token usage.
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    Records privacy-preserving receipts for AI-assisted tasks and enables optional onchain reward claiming via AIPOU tokens. Integrates with MCP-compatible clients like Claude and Cursor.
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    MIT
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    Fast pre-commit dependency gate for AI-assisted code changes. Answers "is this safe to commit?" with a PASS/WARN/BLOCK verdict in seconds, so you can catch risky blast radius before a bad commit, not after it. No database, no heavy setup.
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    MIT
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    A persistent long-term memory system that enables AI clients to store and recall notes, code, and research via semantic search. It utilizes Google Gemini embeddings and Supabase pgvector to provide a secure, searchable 'Second Brain' for MCP-compatible applications.
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    MIT
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    MCP server providing 29 tools across 5 layers for semantic TypeScript/JavaScript code intelligence, enabling AI agents to find references, trace impacts, guard APIs, and explain errors without text-search false positives.
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    MIT
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    Enables users to visualize the impact of edits in internal documents and emails by structuring content as a graph and tracing dependency chains.
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    Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r
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    MIT
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    Structured reasoning MCP server that decomposes problems into atomic steps (premise, reasoning, hypothesis, verification, conclusion) with confidence scoring, live visualization, and approval feedback.
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    MIT
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    Disruption Intelligence MCP gives AI agents access to commercial disruption signals through a public MCP server backed by the hosted Forgemesh API. It supports WARN/layoff intelligence, company context, geospatial territory disruption, x402 payment challenge inspection, and economic signal workflows without exposing private scoring logic, ingestion systems, schemas, or infrastructure.
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    MIT