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

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.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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 capturing a tamper-evident, hash-chained local record of every AI agent tool call — both the decision before a tool runs and its outcome — so you can review what the agent actually did in order, detect edits, deletions, or reordering at the exact index, and export a signed evidence pack any third party can verify with no installs.

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.

It enables agents to discover Rapid7 InsightIDR log sets and logs, run LEQL searches and analytics, and follow paginated results for natural-language investigations.

Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

MCP server for read-only investigation of Aliyun SLS logs fixed to cn-beijing/taient-rpa/node-rpa. Exposes search_logs, get_context_logs, and check_connection tools with a guided investigation skill.

这是面向智能运维场景的 MCP 工具服务，让 Agent 能够按需检索日志内容并获取主机与应用的监控指标数据。它把实时的日志与指标证据接入 Plan-Execute-Replan 诊断流程，从而支撑自动故障排查与根因分析。

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

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.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

MCP server for Beszel system monitoring that provides tools to list systems, containers, alerts, and query CPU, memory, disk, and network stats.

Enables AI assistants to query application projects directly for logs, metrics, incidents, and semantic search through read-only tools.

A read-only MCP server for bounded semantic inspection of ROS 2 perception systems, enabling discovery and metadata extraction from sensors such as cameras, depth sensors, and LiDARs without device configuration or actuation.

Enables read-only observability of Windows systems, exposing CPU, memory, storage, service, and health information through Model Context Protocol tools.

An MCP server for the Liongard platform, providing tools to manage inspectors, systems, metrics, alerts, and environments through Liongard's API.

MCP server providing access to Siemens WinCC V8 SCADA systems via REST API, enabling tag management, alarm logging, and archive operations.

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.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

MCP server for tracing, logging, and debugging multi-agent systems by capturing sessions, spans, and events in a queryable trace tree.

A local MCP server that gives LLMs long-term memory by indexing code, infrastructure, logs, and docs into a queryable graph. It enables semantic and structural search, evidence-backed reasoning, and tracked plans that persist across sessions and teams.

Grades the transmitters and the chain, not just the claim — grade_claim grades a claim against your local rijāl registry (ordinal + provenance, never numeric confidence). AI audit trail for RAG and multi-agent systems.

Enables GPU profiling and performance analysis via NVIDIA Nsight Systems, allowing agents to profile binaries and aggregate statistics for kernels, memory copies, and NVTX ranges. It supports advanced analysis through interval tree construction and structural queries on profiling reports.

An MCP server that exposes RAG search, ServiceNow, and observability tools to MCP clients, and proxies curated calls to remote ServiceNow and observability MCP servers.

An MCP server that helps engineers investigate service incidents using semantic log search, error aggregation, RAG-based diagnosis, and runbook recommendations.

Enables read-only querying and analysis of Azure API Management resources, including API inventories, OpenAPI specs, policies, service health, metrics, gateway logs, and semantic search across the API surface.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

Enables querying logs and metrics with plain SQL from any MCP client via pooml's read-only query API.