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"namespace:io.github.Ansvar-Systems" matching MCP servers:

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    An MCP server that allows users to run and visualize systems models using the lethain:systems library, including capabilities to run model specifications and load systems documentation into the context window.
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    MIT
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    MARM MCP provides persistent memory and structured session context beneath any AI tool, so your agents learn, remember, and collaborate across all your workflows.
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    MIT
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    Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).
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    MIT
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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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    Enables the creation and execution of task-specific AI sub-agents defined in markdown across any MCP-compatible tool like Cursor or Claude Desktop. It integrates with execution engines such as Claude Code, Cursor CLI, and Gemini CLI to provide portable and reusable specialized agent workflows.
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    122
    MIT
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    Provides human-like memory dynamics for AI assistants where memories naturally fade over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve. Enables automatic saving, searching, and management of contextual information with temporal decay algorithms.
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    AGPL 3.0
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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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    MIT
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    Provides access to Swiss livestock regulations and compliance data covering animal welfare standards (TSchV), RAUS/BTS direct payment programs, and TVD movement rules. Enables querying of housing specifications, stocking densities, feed requirements, and breed data for cattle, pigs, poultry, sheep, goats, and horses.
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    36
    Apache 2.0
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    Enables searching and retrieving over 1,100 Zambian statutes and 9,000 provisions directly from AI clients for legal research and compliance. It features full-text search, citation validation, and mapping of Zambian laws to international legal frameworks.
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    Apache 2.0
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    Bridges the Model Context Protocol with Language Server Protocol to provide AI agents with persistent access to code intelligence features including navigation, diagnostics, refactoring, and completion across 7+ programming languages.
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    2,885
    MIT
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    Enables users to search, retrieve, and validate over 11,000 Philippine statutes and nearly 100,000 provisions through AI-powered legal research tools. It supports full-text search across Republic Acts, the Constitution, and various codes while providing cross-referencing and international law alignment capabilities.
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    Enables querying of Swiss farm workplace safety regulations including BUL/SPAA rules, Suva occupational requirements, EKAS standards, and Agriss accident statistics. Provides tools for risk assessments, machinery safety compliance, chemical exposure limits, young worker protections, and accident reporting guidelines.
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    31
    Apache 2.0