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"A server that supports Server-Sent Events (SSE)" matching MCP servers:

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    Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.
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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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    Python MCP server for GitHub operations, providing native tool integration with Claude Code and other MCP clients. It enables managing issues, pull requests, CI status, milestones, and batch operations via natural language.
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    MIT
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    A comprehensive MCP server for Dokploy that provides 14 action-based tools covering the full DevOps lifecycle with minimal token usage. It enables AI assistants to manage projects, applications, databases, domains, servers, and more through a unified interface.
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    MIT
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    Connects AI assistants to GitLab to interact with merge requests, reviews, discussions, pipelines, and test results through natural language queries. Supports viewing MR details, responding to comments, checking test summaries, and analyzing job logs.
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    A local MCP server that exposes Bazel build system functionality to AI agents, allowing them to build, test, query, and manage Bazel projects through natural language even in environments where Bazel can't be directly accessed.
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    MIT
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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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    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
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    Enables comprehensive Jenkins automation through MCP interface, allowing users to manage builds, jobs, artifacts, and queues with natural language commands. Supports build triggering, monitoring, artifact retrieval, and system status checks with automatic CSRF protection and authentication.
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    MIT