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    MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.
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    Apache 2.0
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    Enables AI assistants to deploy, manage, and rollback websites via the Krexel API, supporting site uploads, deploys, logs, rollbacks, environment variables, and status checks.
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    MIT
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    Connects Claude to SAP Cloud Platform Integration (CPI) to diagnose failed messages, review iFlows, deploy artifacts, and check credentials directly from your conversation.
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    MCP server for GitFlic, the Russian Git hosting platform, enabling AI agents to manage projects, issues, merge requests, files, and more via 66 tools covering 13 API categories.
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    Apache 2.0
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    Enables AI assistants to manage and operate Venelx CI/CD pipelines through the Venelx REST API, including listing projects, triggering builds, checking status, tailing logs, accessing artifacts and workers, and diagnosing signing or GitHub access.
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    Enables monitoring and analysis of Ansible playbook executions through the Ara Records API. Provides real-time playbook monitoring, task progress tracking, and comprehensive access to Ansible execution data.
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    MIT
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    Enables AI assistants to review GitLab merge requests by fetching changes, analyzing diffs, adding comments, and managing approvals through the GitLab API. Supports complete merge request analysis, file-specific reviews, and version comparisons.
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    MCP server for the Bitbucket Cloud REST API v2.0, providing 32 tools across 5 toolsets for repository management, pull requests, issues, pipelines, and more with safety controls and LLM-optimized output.
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    Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.
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    MIT