"Understanding Frontend and Backend Development" matching MCP servers:

Enables AI agents to read Microsoft Fabric lakehouse or warehouse tables, infer keys and relationships, and create or update a GraphQL API item — returning a ready endpoint for Lovable, Cursor, or Claude Code. It also plans and validates schemas and drafts companion artifacts such as semantic models, dbt sources, join paths, and data dictionaries, with dry-run defaults.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Enables users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

MCP server for FormsList, a form-backend SaaS. Enables creating form endpoints, reading submissions, configuring auto-responses, and generating embed snippets via natural language.

Enables coding agents to interact with Metaflow workflows, including querying flows, runs, tasks, logs, and artifacts across any Metaflow backend.

Enables creating and inspecting Seed tables and relationships through the Seed backend HTTP API.

Enables structured document understanding of local PDFs via a dual-extract MCP server, combining MinerU text/layout and Qwen3-VL vision with fusion adjudication for field extraction, tables, formulas, and validation. Fully local and offline.

Enables comprehensive interaction with DHIS2 health information systems through 40+ tools covering complete Web API functionality. Supports data management, tracker programs, analytics, and bulk operations for DHIS2 development and administration.

Enables large language models to retrieve up-to-date and correct information about dlt pipelines, datasets, and schemas, improving AI-assisted development.

Exposes ERP data (production orders, inventory, BOM, customers) to any MCP client through a backend-neutral interface, with a mock backend for testing.

Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.

Enables data engineers and BI professionals to perform data pipeline development, quality assurance, visualization, and API integration locally with AI assistance.

Enables an agent to author StageFlow pipelines as JSON and check them against a live backend — its schema, stages, node types and plan ceilings — before spending a run, then execute or stop them and read back status, results, artifacts, meters and the node path a run took. It also exposes the same graphs to an open editor canvas and, when the backend asks, gathers the backend address through the client's own prompt rather than the conversation.

Enables Claude, Cursor, VS Code, ChatGPT and other MCP clients to analyze Google Search Console, Google Ads and AdSense data through 57 read-only tools covering search performance, indexing, wasted ad spend, quality scores, earnings and combined paid-vs-organic insights. Runs as a thin local client against a hosted backend, so no Google Cloud project, OAuth client or developer token is needed.

Connects external APIs like Open-Meteo and AgroMonitoring to your development environment through URI-like requests, allowing access to live data directly in MCP-compatible tools.

Turns existing backend APIs (OpenAPI) and SQL databases (PostgreSQL, MariaDB, ClickHouse) into hosted MCP servers for AI clients, with built-in dashboards, forms, and credential encryption.

Provides deterministic tools for understanding, transforming, and verifying structured data via MCP, enabling rule inference from examples and verification of transformed records.

A unified backend MCP server that aggregates and filters data from external services like Zaim, GitHub, Google, and Notion, providing cross-cutting views via MCP and REST API without heavy AI inference.

Enables AI agents to query and operate on ERP data through a unified tool interface, working across CSV exports, SFTP drop folders, SQLite/ODBC, and optional enterprise APIs. It supports purchase orders, vendors, and inventory lookups while keeping agent-facing tools consistent regardless of backend.

Exposes an agentic AutoML pipeline as a callable tool so any MCP client can upload a CSV and natural language goal and receive a full ML analysis report with SHAP visualizations. Enables autonomous problem understanding, data cleaning, feature engineering, model training, and explainability through a single remote tool call.

Backend MCP server for the Expenses Tracker app, providing APIs to record, retrieve, and report expenses.

Provides 12 MCP tools to directly interact with DEM MDM backend API, enabling Cursor or AI agents to manage MDM data.

Enables AI agents and backend integrations to query multi-market financial data, technical indicators, fundamentals, money flow, news, and filings, and export structured CSV/JSON through MCP tools and HTTP APIs.