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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.
    2
    14
    MIT
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    Facilitates spec-driven development workflows by providing structured prompts for generating requirements in EARS format, design documents, and implementation code following a systematic approach.
    74
    437
    MIT
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    An MCP server that integrates AI assistants like Claude with GitLab's merge requests, allowing them to review code changes, add comments, and approve/unapprove merge requests directly through the GitLab API.
    45
    MIT
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    MCP server for E2B code sandbox, enabling creation, management, and execution of code in secure sandboxes using Python and shell commands.
    4
    1
    MIT
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    A lightweight Model Context Protocol (MCP) orchestrator designed for efficiency at scale. It features TOON compression (reducing token usage by 30-90%) and Lazy Loading, making it the ideal solution for complex, multi-tool agentic workflows.
    9
    16
    13
    MIT
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    A MCP server for managing and storing code snippets in various programming languages, allowing users to create, list, and delete snippets via a standardized interface.
    3
    16
    7
    MIT
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    An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.
    8
    36
    186
    MIT
  • F
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    An orchestration platform for deploying parallel swarms of tool-enabled AI agents to perform complex tasks like code generation, system monitoring, and multi-perspective analysis. It features a unique chunked write pattern that enables the creation of large-scale documents and code files by assembling parallel agent outputs.
    25
    7
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  • F
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    An MCP server that enables AI agents to execute terminal commands and Python code on the host system, leveraging Agent Zero's battle-tested implementation with session management and smart output handling.
    4
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    Enables AI coding agents to generate standardized code using scaffolding templates, enforce architectural patterns, and validate outputs programmatically. Supports creating projects from boilerplates and adding features to existing codebases while maintaining team conventions.
    161
    AGPL 3.0
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    Enables AI coding assistants to query a persistent local code graph for targeted context, blast-radius analysis, and incremental updates, so they read only relevant files during reviews and large-repo workflows.
    MIT