"Kotlin RAG (Retrieval-Augmented Generation) implementation resources" matching MCP servers:

A black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.

A modular Retrieval-Augmented Generation (RAG) framework that provides hybrid search and knowledge retrieval capabilities via the Model Context Protocol. It enables users to integrate document-based knowledge into LLM workflows with support for dense/sparse retrieval, reranking, and observability.

Exposes knowledge retrieval to AI tools over MCP with dense, sparse, and hybrid search, RRF fusion, configurable reranking, and modular ingestion of PDF/Markdown documents including image captioning. It also provides query tracing and Ragas-based evaluation so pipelines can be swapped, debugged, and tested independently.

Enables cloud and platform engineers to investigate AWS incidents by grounding responses in approved runbooks and operational evidence, with authenticated access, citations, observability, and human approval before any write action.

Enables AI agents to build, test, debug, and interact with Kotlin Multiplatform Mobile (Android/iOS) applications through automated build pipelines, UI automation, crash analysis, and app state inspection.

Honeycomb MCP (Model-Controller-Presenter) Server implementation

Enables plant operators to query alarm data, asset information, trends, correlations, and operator recommendations through 14 tools, forming a core part of a multi-MCP enterprise operations copilot.

The implementation of Model Context Protocol (MCP) server for VictoriaLogs.

The implementation of Model Context Protocol (MCP) server for VictoriaMetrics

Enables LLM evaluation and observability by uploading documents, building test sets, running RAG pipelines, and automatically scoring answers for groundedness, hallucination risk, retrieval quality, latency, and cost, with tools exposed to MCP-compatible clients.

An extensible MCP hub that exposes internal services (chat, observability, RAG) as namespaced tools via FastMCP, with OpenAPI auto-generation, auth, and resilient error handling.

A Model Context Protocol (MCP) server implementation for Humio, enabling integration with Humio's logging and analytics platform.

Enables agents to autonomously investigate deployment health by inspecting Kubernetes resources, comparing live cluster state against Git, and correlating findings with Dynatrace problems.

Exposes network-monitoring tools (query metrics, analyze windows, compare, logs, status, runbooks, speed tests) as an MCP server for agentic workflows. Designed with evaluation suites, cost-aware model routing, and semantic tool retrieval.

MCP server for semantic log ingestion, hybrid retrieval, and cleanup, enabling natural-language querying of log files with dense+BM25 retrieval and full provenance.

Enables read-only querying of Grafana Loki logs through tools like label discovery, LogQL queries, and recent log retrieval, without requiring knowledge of the Loki API.

MCP server that exposes OSSEC HIDS security monitoring capabilities as tools, resources, and prompts for AI assistants.

MCP server for XXL-JOB Admin that enables AI assistants to manage scheduled jobs through natural language, including task lifecycle management, manual triggering, cron preview, and execution log retrieval.

Enables causal root cause analysis with 56 tools covering causal graph construction, 10 RCA model families plus 3 dedicated PyRCA algorithms (Salesforce PyRCA, BSD-3-Clause), multi-model consensus, and PDF/HTML/Excel/Markdown report generation. Works with Claude, Ollama, Groq, OpenAI, Gemini, LangChain, Cursor — 10 providers.

Cross-cloud observability for AI agents. Discover resources, correlate logs, and diagnose infrastructure issues across AWS, GCP, Vercel, and Cloudflare — without leaving your editor.