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    Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.
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    Apache 2.0
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    Enables LLM agents to interact with the Lean theorem prover through the Language Server Protocol, providing tools for analyzing Lean projects, accessing diagnostics, goal states, documentation, and searching for theorems using both local and external search services.
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    MIT
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    MCP server for AI agents handling EOR & global hiring conversations. 8 tools: country EOR briefs, misclassification risk, EOR vs entity calculator, termination rules, statutory benefits, work visa paths, objection handlers.
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    MCP server that keeps language server sessions warm and routes multiple languages through one process. Agents get persistent cross-file awareness, speculative execution (simulate edits before writing to disk), and 20 skills that encode correct multi-step operations like safe rename, blast-radius analysis, and end-to-end refactoring. Single Go binary, no runtime dependencies.
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    MIT
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    An intelligent agent that responds to financial queries about TreePod Glamping directly within Claude Desktop using MCP protocol, providing tools for tariff calculation, occupancy checking, financial analysis, and business reporting.
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    Merx - TRON Resource Exchange Merx is the first TRON resource exchange that aggregates energy and bandwidth providers into a single MCP server. GitHub: https://github.com/Hovsteder/merx-mcp Hosted SSE: https://merx.exchange/mcp/sse npm: merx-mcp Website: https://merx.exchange Stats * 52 tools, 30 prompts, 21 resources * 7+ energy providers (CatFee, ITRX, PowerSun, Fe
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    MIT
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    Provides persistent personal and organizational knowledge storage that any LLM can connect to for instant context about who you are, what you do, and your preferences. Enables AI agents to maintain long-term memory across sessions through structured data categories, semantic search, and export/import capabilities.
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    Hey @roocode community! I'm thrilled to share a project born from my work with Roocode and the vision of an AI-powered development team: the Anubis MCP Server! This system is heavily inspired by Roocode and designed to orchestrate an AI development workflow based on agile methodology. It simulates
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    MIT
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    An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.
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    Provides persistent memory for AI models by enabling the storage and retrieval of episodic, semantic, and procedural information through the memro protocol. It allows assistants to maintain long-term context via semantic search and chronological memory management.
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    MIT
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    TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.
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    Apache 2.0