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    Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.
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    MIT
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    More than just an MCP server that covers the entire range of Docker management tasks, it helps you create workflows to easily manage your Docker environments at scale. It allows you manage multiple local or remote (TCP, TLS, SSH) docker instances and exposes things like logs and stats as resources so that you can monitor and triage all of them.
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    MIT
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    Universal Docker MCP server for AI assistants (Cursor, Claude Desktop). Manage Docker containers, execute commands, query databases, and handle environment configurations — all through natural language.
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    MIT
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    Enables AI assistants to manage Docker containers, images, networks, volumes, and Compose services through the Model Context Protocol. It supports system operations, command execution within containers, and integration with Docker Hub and GitHub Container Registry.
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    MIT
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    Docker Helper MCP server that provides tools for automating Docker tasks such as generating Dockerfiles, parsing docker-compose files, and optimizing images.
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    MIT
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    Deterministic US equity-compensation tax optimizer. Six tools cover ISO/AMT exercise scheduling, NSO sell-vs-hold, RSU vest-and-sell, single-stock concentration, protective put / zero-cost collar pricing, and Section 1202 QSBS qualification. Federal plus 50-state plus DC tax math.
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    MIT
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    A fault-tolerant, stealth-enabled Model Context Protocol (MCP) server for web searching and content fetching. Built for AI Agents (Cursor, Claude Code, OpenCode), it uses a stealth browser engine to fetch pages, dynamically handles SPAs/React, and converts bloat into token-optimized Markdown.
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    CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.
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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
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    Self-contained SearXNG MCP server in Docker. Aggregates 200+ search engines across 30+ categories with multi-page fanout, autocomplete, and engine discovery. Dual transport (HTTP + stdio), API key auth, and built-in Web UI reverse proxy.
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    MIT
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    Read visual bug reports from Feedbug in your AI coding agent: screenshot, console logs, failed network requests, session replay and the DOM context of the element the tester clicked. Trace the bug to its source file, comment and resolve without leaving the editor.
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    MIT
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    An MCP server that loads your Ditto profile, mined from your local Claude Code, Codex, and OpenCode session logs, so your agent works like you. Exposes the load_ditto_profile tool over the Model Context Protocol.
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    Local MCP server for validating EU VAT numbers using the official VIES API. Enables AI to check VAT validity and optionally retrieve consultation numbers for legal proof.
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    MIT
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    Enables interaction with Jira Service Management Operations alerts and on-call schedules, including searching alerts, reading notes and activity logs, acknowledging, closing, annotating, adding responders, and querying current and next on-call rotations.
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    Apache 2.0
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    Compares AI coding tool spend before and after a migration -- Cursor, Claude Code, GitHub Copilot, OpenCode, Codex CLI -- via an MCP server, real numbers from each vendor's own API or local logs.
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    Apache 2.0
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    Zero-config SQL profiler for slow Python/SQLAlchemy jobs, built for agents: returns the exact call site, query count, and fix as compact machine-readable fields instead of raw query logs~55× fewer tokens per diagnosis (≈10k → ≈180) and the matching drop in API cost.
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    MIT