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    LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.
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    8
    MIT
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    The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.
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    399
    MIT
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    Single-binary Go MCP server that wraps whatsmeow to expose a personal WhatsApp account as 41 MCP tools (messaging, groups, polls, media, privacy).
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    5
    MIT
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    Manage your entire notification infrastructure using natural language. Trigger workflows, create users, manage preferences, update tenant branding, and access docs — all from Cursor, Claude Desktop, or Windsurf. 24 tools covering email, SMS, push, WhatsApp, Slack, MS Teams, and in-app notifications.
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    12
    MIT
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    MCP server that reads Duplicacy backup metrics from a Prometheus exporter and exposes them to LLMs for monitoring backup status, progress, and health.
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    4
    119
    2
    GPL 3.0
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    A Model Context Protocol (MCP) server for Grafana. This provides access to your Grafana instance and the surrounding ecosystem.
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    3,279
    Apache 2.0
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    Enables AI assistants to query databases using natural language, with automatic schema discovery and SQL compilation.
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    843
    3,130
    Apache 2.0
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    Enables SQL queries against PostgreSQL databases through MCP-compatible clients and includes a natural language agent for forming SQL queries from natural language.
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    203
    PostgreSQL
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    A Model Context Protocol server implementation for Axiom that enables AI agents to query your data using Axiom Processing Language (APL).
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    60
    MIT
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    This project implements a simple MCP server in Go that exposes a single tool (create_short_link) to generate short URLs using the Rebrandly API.
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    MIT
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    Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.
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    MIT
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    Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.
    Last updated
    17
    MIT