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    Enables AI coding agents to retrieve the latest stable versions of packages and tools across multiple ecosystems, preventing outdated dependency versions in generated code.
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    Apache 2.0
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    Safe-upgrade advisor for OpenClaw. Detects current version, checks the deployment against a hand-curated catalog of version-specific known regressions, captures pre-upgrade snapshots, diffs them against post-upgrade state, and emits step-by-step upgrade + rollback guides.
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    MIT
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    Enables AI assistants to set up, run, and manage Ballerina + Salesforce integrations inside a WSO2 Integrator workspace, providing 18 tools for OAuth2 token acquisition, project scaffolding, building, deploying, and stopping the integration service.
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    A secure MCP server providing read-only access to Argo CD instances using browser session cookies, enabling querying of applications, projects, clusters, and repositories.
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    MIT
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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 monitoring and control of the SST development process by streaming dev logs, managing Lambda invocations, and executing lifecycle commands like start, stop, and restart. It provides real-time access to event streams and deployment status directly through the Model Context Protocol.
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    A modular MCP server that provides a unified interface for interacting with GitHub and GitLab, including enterprise and self-hosted instances. It enables comprehensive management of repositories, issues, pull requests, and CI/CD pipelines through natural language.
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    MIT
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    Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.
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    MIT
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    The Model Context Protocol (MCP) Jenkins integration is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.
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    MIT
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    Enterprise-grade MCP server exposing Ansible Automation Platform 2.x as a complete AI interface for LLMs, enabling natural language management of automation resources.
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    Apache 2.0