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    A local AST and type-aware Go repository context indexer that uses CHA to map symbols, call graphs, dependencies, and architecture patterns. Built for AI coding agents that need to navigate and reason about large Go codebases without reading raw files.
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    MIT
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    Scans source code for possible Korean compliance risks (PIPA, Network Act, Credit Information Act, E-Commerce Act) and maps findings to specific legal provisions. Runs locally, exposes MCP tools for scanning and law lookup, and does not constitute legal advice. That's hedged (matches the project's "possible risk / not legal advice" rule), keyword-rich for search, and names all four laws.
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    MIT
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    Persistent, consensus-validated institutional memory for AI agents. Gives LLMs real memory that survives across sessions - validated through BFT consensus, not just dumped to a file.
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    Apache 2.0
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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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    About The fast, idiomatic way to build MCP servers in Go. Gin-like DX with struct-tag auto schema, middleware, adapters for Gin/OpenAPI/gRPC.
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    Apache 2.0
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    Adds security capabilities like port scanning, TLS inspection, DNS enumeration, process monitoring, secrets scanning, HTTP header auditing, and CVE checking to Claude Code and Cursor.
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    Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.
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    Enables users to interact with container registries through the ORAS CLI, providing information about container images, platforms, and signatures via natural language queries.
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    Apache 2.0
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    Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON
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    Connect AI agents like Claude, Cursor, and Gemini to historical Windows performance and privacy data gathered by the AppControl Windows app. This server enables natural language queries into CPU, GPU, and temperature history alongside system security events for deep local auditing.
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    Coordination layer for AI coding agents working on the same codebase. Adds file locks, shared project memory, and cross-machine file sync so Claude Code, Cursor, Windsurf, and other MCP agents stop overwriting each other.
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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.
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    MIT
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    Query WHOIS/RDAP information for domains, IP addresses, CIDR prefixes and ASNs. Results are normalized to RDAP-style (RFC 9083) JSON. Public instance of the open-source KincaidYang/whois server, which can also be self-hosted.
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    MIT
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    Simple MCP Runner makes it effortless to safely expose system commands to language models via a lightweight MCP server—all configurable with a clean, minimal YAML file and zero boilerplate.
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    MIT
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    Resolves desktop and brand icons to local file paths for use in Waybar, Rofi, scripts, and AI agents via an MCP stdio server with tools for resolve, prefetch, cache, sources, packs, and overrides.
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    MIT
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    A lightweight, zero-agent SSH operations tool that enables remote command execution, file transfer, and audit logging. It integrates as an MCP server for AI-driven infrastructure management.
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    MIT