"RAG MCP servers with quality validation" matching MCP servers:

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

Enables AI agents to screen and filter stock universe, compute custom quality scores, inspect score history, manage scoring systems, and generate shareable screen links, acting as the signed-in user.

Validates MLCommons Croissant dataset metadata (JSON-LD) for schema compliance, as a stateless MCP server.

A tool that enables automated browser control using Pyppeteer within the MCP framework, allowing navigation, screenshot capture, and element interaction with websites.

The MCP server provides tools for entity extraction, query refinement, and relevance checking to enhance RAG applications by integrating with OpenAI and Gemini.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.

Enables AI-assisted Attribute-Based Access Control code validation and review, with batch processing and progress notifications for long-running operations.

Enables notes management, weather and news search, document ingestion and RAG-based semantic search using GroundX, with OpenAI GPT integration for summarization and completions.

Audits your Claude Code memory store with 4-dimension quality scoring and actionable cleanup recommendations, including a visual dashboard.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Automatically enhances user prompts by applying expert-level prompt engineering techniques tailored to technical, creative, or analytical content types. It provides visual feedback on applied optimizations to ensure higher quality, structured, and more comprehensive AI responses.

Validates phone numbers worldwide (carrier, line type, country) via single or batch requests, with pay-per-call using x402 micropayments (USDC on Base) — no API key required.

Enables autonomous data quality inspection and repair workflows. It scans DuckDB warehouses for anomalies, generates and verifies fixes in a dry-run copy, then applies them after validation, with full audit logging.

Automates repository analysis, test planning, and generation of end-to-end tests with Playwright, acting as an intelligent quality assistant.

This MCP server provides a modern web interface and a set of tools for interacting with the Facebook Marketing API, enabling campaign management, ad set operations, and insights retrieval. It supports multiple connection modes including STDIO, SSE, and HTTP.

A learning MCP server that demonstrates tools and resources using FastMCP, with a greet tool and UI capabilities.

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Provides deterministic Python code quality analysis using flake8, mypy, McCabe, and vulture, enabling LLMs to access real linting and type checking results.

Generates precise, measurable quality evaluation standards and scoring criteria for any task, transforming vague requirements into specific dimensions that guide execution and improve work quality.

Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.