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

A production-ready MCP agent that helps data teams define, validate, and visualize semantic metrics with enterprise-grade persistence, trust scoring, and BI integrations.

Enables data teams to define and validate metrics through conversation, inspect trust scores and lineage, and export definitions to Looker, Tableau, and dbt.

Connects Google Search Console to AI assistants, enabling SEO data analysis through natural language conversations.

Enables searching Google Scholar papers with year filtering, deduplication, and proxy support. Also provides paper detail retrieval, TF-IDF relevance analysis, and chart generation via MCP tools.

Integrates with Google Search Console to enable querying search analytics, comparing performance periods, generating visual reports, and identifying SEO optimization opportunities through natural language.

An MCP server that enables AI agents to compile, refine, and interlink knowledge into a persistent wiki, replacing RAG with structured, curated knowledge.

A read-only, cross-platform visualization layer for Cortex that renders memory, sessions, and code into six live reading angles (graph galaxy, 3D anatomical brain, execution trace, consolidation board, knowledge browser, and wiki) without ever writing a memory.

Enables discovery of Fabric/Power BI workspaces and semantic models, execution of DAX queries, and generation of executive HTML reports with visualizations.

Enables AI assistants to interact with inSCADA systems via the Model Context Protocol, providing 39 tools for live data, alarms, scripts, historical analysis, charts, and more.

Enables AI agents to author and edit Power BI files locally (.pbix/PBIP), covering semantic models, reports, and Power Query M with 490 tools.

Eleven local stdio MCP servers exposing a reproducible EPA SWMM stormwater-modelling workflow: model building, simulation with run manifests and continuity checks, calibration, GIS/QGIS, design storms and climate scenarios, uncertainty analysis, plotting, and modelling memory.

Transforms markdown documents into immersive 3D visualizations using semantic analysis and spatial layout, enabling navigable knowledge structures.

MCP server for semantic spreadsheet operations that lets LLMs create and edit Excel workbooks by describing spreadsheet intent.

Creates, inspects, validates, and modifies Power BI Project (.pbip) folders, generating PBIR-style reports and TMDL semantic models from structured inputs.

Local-first MCP server for Power BI Desktop automation. Automate semantic model changes, DAX, Power Query, Excel, and report layout from MCP-capable AI clients.

Provides advanced charting widgets (uPlot time series, ECharts box plots and parallel coordinates) for Urano Desktop/Cloud via MCP tools that build uiSpec JSON for rendering.

Give AI agents access to Formester form submissions. Read individual responses, search and filter across forms, write AI-generated insights back as custom fields, and process file attachments including PDFs and images.

Consolidated MCP server exposing 161 tools across 9 groups to manage a layered data platform (financial, economic, statistical) backed by a single SQLite file, with data fetching delegated to an upstream semantic fetcher.

A TypeScript/Node.js MCP server that wraps the Metabase REST API, enabling AI agents to execute queries, explore schemas, and build dashboards through structured tool calls.

Provides football analytics tools including player scouting, comparisons, market-value filters, expected-goals tables, match-by-match form, team attacking profiles, match search, shot maps, and more for 10 leagues.