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    A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.
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    MIT
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    Git-native long-term memory for AI agents: your markdown files are the source of truth, the search index is a disposable projection rebuilt from git, and every memory the agent writes is a reviewable git commit. Served over one OAuth-secured MCP endpoint with hybrid lexical+semantic recall and a gated, git-first commit_note write tool.
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    AGPL 3.0
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    A Model Context Protocol server that provides persistent storage, categorization, and retrieval of bookmarks through AI clients like Claude. It allows users to manage web links using custom categories and includes options for local JSON storage or AWS S3 synchronization.
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    Apache 2.0
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    Live Japan seasonal travel data from Japan Meteorological Corporation. 12 tools covering cherry blossom (sakura) forecasts, autumn leaves (koyo), fruit picking, flowers, festivals, and 3-day weather. 1,700+ GPS-tagged spots updated daily at 9AM JST. Works via npx or hosted HTTP endpoint — no auth required.
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    MIT
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    Operations toolchain for SQLite, Cloudflare D1, and Turso. Every command is available as both a CLI and an MCP tool: inspect, diff, migrate, monitor, back up, and repair databases. 22 stdio tools, read-only by default.
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    AGPL 3.0
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    The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.
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    MIT
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    mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str
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    MIT
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    Track how your brand appears in AI-generated answers across ChatGPT, Perplexity, and other AI models. Analyze visibility, sentiment, citations, and domain rankings with 31 tools — including analytics reports, chat inspection, query analysis, and full CRUD for brands, prompts, tags, and topics.
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    MIT
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    A smart AniList integration for the Model Context Protocol that provides AI assistants with tools for searching media, managing watchlists, and analyzing user anime or manga tastes. It goes beyond basic API calls by offering personalized recommendations, taste comparisons, and natural language profile summaries.
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    MIT
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    DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.
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    MIT
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    An MCP server that enables users to retrieve YouTube transcripts and perform video or channel searches without requiring Google API keys. It supports transcript chunking and provides tools for detailed video content analysis and channel metadata extraction.
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    MIT