"Semantic search, RAG, and memory systems" matching MCP servers:

This MCP server enables intelligent API testing automation by combining RAG knowledge retrieval with tool execution capabilities. It allows QA engineers to perform natural language-driven API testing with contextual knowledge support.

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.

Enables AI agents to retrieve the latest semantic version tags for container images from Docker Hub, GHCR, Quay, and other OCI registries, allowing them to pin specific versions for reproducible deployments.

A comprehensive and efficient Model Context Protocol server for task management that works with Claude, Cursor, and other MCP clients, providing powerful search, filtering, and organization capabilities across multiple file formats.

Enables AI systems like Claude and Cursor to directly manage Railway projects, deployments, services, environment variables, and monitor logs through natural language commands.

Enables interaction with GitHub repositories, issues, pull requests, code search, branches, and GitHub Actions workflows.

Enables searching, reading, and analyzing discussions on GitLab's community forum for troubleshooting CI/CD issues and GitLab features. Pre-configured with GitLab-specific search filters and optimized workflows for support scenarios.

Enables interaction with Bitbucket Cloud through 25+ tools for managing repositories, pull requests, branches, commits, issues, pipelines, and code search with OAuth 2.0 authentication.

Enables intelligent access to AL-Go documentation, workflows, and domain expertise for Business Central development automation through specialized personas and cross-source semantic search.

A fully-featured GitLab MCP server that provides 25 advanced capabilities for interacting with GitLab via REST API, including repositories, merge requests, issues, and global search.

Provides AI assistants with full access to Jenkins CI/CD systems, enabling querying, managing, and controlling Jenkins jobs, builds, nodes, and queues through natural language.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

A production-ready template for building Model Context Protocol (MCP) servers in Python, using Docker Compose for containerized development and CI/CD.

Enables interaction with Jenkins instances to manage jobs, builds, and nodes through the Model Context Protocol. It provides capabilities to trigger builds, read console outputs, and search log sections using regular expressions.

Enables AI coding assistants to search reproducibly verified bug fixes, compatibility recipes, and code patches, and to submit new solutions for automated sandbox verification.

Enables comprehensive DevOps infrastructure management through tools for Jenkins, Ansible, Terraform, Kubernetes, and Docker operations. Features a sophisticated memory system for context retention and provides validation, generation, and optimization capabilities across DevOps workflows.

A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.

A production-grade MCP server providing 18 tools for comprehensive GitHub interaction, including repository management, issues, pull requests, code search, and CI/CD status, with Redis caching and rate limit handling.

A Model Context Protocol server for managing and executing dbt Cloud jobs via Claude, with search, run history, and job triggering capabilities, including safety confirmations.

Enables cross-session memory, weighting, and factory/PR/artifact linking for CIC agents, aggregating multiple sessions to identify promotion candidates.