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    Enables Claude to function as a full-stack software engineer with comprehensive development capabilities including project creation, database management, frontend/backend development, testing, deployment, and DevOps operations across multiple frameworks and technologies.
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    An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.
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    MIT
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    SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.
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    MIT
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    Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.
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    MIT
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    A Model Context Protocol (MCP) server for LocalStack that enables management of local AWS development environments, including container lifecycle operations, infrastructure deployments, log analysis with IAM policy generation, chaos injection, and Cloud Pods state management.
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    Apache 2.0
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    An MCP server that automates the full software development lifecycle through an AI-driven TDD state machine. It handles everything from task decomposition and test-driven development to integration testing and automated pull request creation.
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    Enforces authorize-before-execute for any MCP-compatible AI agent. Exposes atlasent_evaluate and atlasent_verify_permit tools so a protected tool call only runs after AtlaSent issues and verifies a signed, single-use permit — fail-closed on any error, timeout, or malformed response.
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    MIT
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    A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.
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    Enables AI coding assistants to interact with JetBrains TeamCity CI/CD server through natural language commands. Supports triggering builds, monitoring status, analyzing test failures, and managing build configurations directly from development environments.
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    MIT
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    Connects AI tools directly to Codemend production error monitoring to list, analyze, and resolve software crashes. It enables users to retrieve AI-generated fixes and automatically open GitHub pull requests to address production issues.
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    MIT