"Setting up a streamable HTTP server" matching MCP servers:

Enables interaction with Jenkins servers through HTTP APIs, allowing users to list jobs, trigger builds, view logs, and manage configurations without requiring plugins or admin access.

A generic template for building remote MCP servers based on Streamable HTTP, with a demo ping tool and infrastructure for authentication, logging, testing, Docker, and CI/CD.

Enables GitHub operations via MCP, providing tools for issues, pull requests, and Actions workflows through a Streamable HTTP transport.

Enables AI agents to deploy static files and get live HTTPS URLs instantly, with support for custom domains and data residency.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

A CircleCI MCP server specialized in config review, providing tools for fetching actual configs, validating changes, and analyzing workflow bottlenecks, health, and DAG dependencies.

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.

A production-ready MCP server for Jenkins that enables managing jobs, pipelines, builds, and nodes through natural language, with configurable security and guardrails.

MCP security trust layer. Continuously monitors 800+ MCP packages on npm for install scripts, command injection, hardcoded secrets, capability drift, and publisher posture. Ships a GitHub Action policy gate for PR-level allow/warn/block decisions. 5 MCP tools, no API key required.

An MCP server that gives AI agents full access to the Harness.io platform through 11 consolidated tools and 207 resource types.

This MCP server lets you use Cursor IDE, or any MCP Client enabled agent, to use natural language to accomplish things with CircleCI, e.g: Find the latest failed pipeline on my branch and get logs

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.

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.

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.

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.

A TypeScript starter template for MCP servers with CI/CD, OIDC npm publishing, and zero-secret setup.

Enables Claude to interact with Infracost for Terraform cost estimation and cloud governance. Supports generating cost breakdowns, comparing configurations, creating tagging policies, setting up cost guardrails, and posting cost comments to PRs.

Exposes a Jenkins controller's REST API to MCP-compatible clients, enabling job management, build triggering, and log retrieval through natural language.

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.

Enables management of Amazon Managed Workflows for Apache Airflow (MWAA) environments and operations including DAG management, workflow execution monitoring, and access to Airflow connections and variables through a unified interface.