"Documentation for Vercel AI SDK" matching MCP servers:

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.

A stdio MCP server exposing a validate_emails tool that lets agents screen email lists without sending mail or probing SMTP, checking syntax, DNS/MX records, disposable domains, role accounts, free providers, typo suggestions, and SPF/DMARC. Each address comes back with a valid/risky/invalid/unknown verdict plus machine-readable reason codes so agents can clean leads and signups before outreach or import.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

A read-only MCP server that reports BI pipeline readiness, blockers, and the next allowed action for governed Power BI workflows. It never writes files, executes warehouse work, or grants human approvals.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

A Model Context Protocol (MCP) server that integrates the FAIM time series forecasting SDK with any MCP-compatible AI assistant, enabling AI-powered forecasting capabilities.

Enables AI coding agents to import xlsx config tables, audit growth curves, run battle and gacha simulations, and reverse-engineer game spreadsheet formulas through 17 read-only tools backed by deterministic, zero-dependency pure-function engines.

A tutorial implementation MCP server that enables analysis of CSV and Parquet files. Allows users to summarize data and query file information through natural language interactions.

Enables unified querying of GA4, Cloudflare Web Analytics, Vercel Analytics, and Google Search Console through a single MCP interface, with cross-tracker comparisons and discrepancy reporting.

Enables AI assistants to interact with Databar.ai's data enrichment API, allowing discovery, configuration, and execution of data enrichments across hundreds of providers using natural language.

Enables agents to validate governed data records, map every value to installed target formats with per-value fidelity and Exceptional Value reporting, and inspect hash-chained audit logs. It supports outbound mapping workflows through the Model Context Protocol.

It gives Claude Code, Cursor, and Codex structured workflows and an MCP server for building data pipelines with dlt - covering REST API ingestion, transformations, data quality, and exploration.

Enables LLMs to interact with Google Analytics Admin and Data APIs to retrieve account summaries, property details, and custom metrics. It allows users to run core and real-time reports to analyze website performance and configuration via natural language.

Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.

Provides AI assistants with access to Vega-Lite documentation, visualization examples, and specification validation tools. Enables searching docs, retrieving examples by category, validating JSON specs, and accessing schema information for creating data visualizations.

Provides MCP tools for AI assistants to retrieve compact daily futures data packets, submit manual market data, run whitelisted crawlers, search research summaries, and save/read historical reports on demand for caustic soda, PVC, and coking coal futures.

An MCP server that integrates with Hunter.io API to find and verify email addresses using domain and name information.

Enables analysis and retrieval of JEFit workout data through natural language. Provides access to workout dates, detailed exercise information, and batch workout analysis for fitness tracking and progress monitoring.

Enables AI assistants to explore and query SAP BW/4HANA modeling objects and metadata, such as InfoAreas, InfoObjects, ADSOs, CompositeProviders, and Queries.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

Enables interaction with the Morpho GraphQL API, providing tools for accessing market data, vaults, positions, and transactions through a Model Context Protocol (MCP) server.

A resilient MCP server wrapping FiinQuant/FiinQuantX Python SDK for Claude Desktop and Cursor, providing market data, fundamental analysis, screening, and technical indicators via stdio with timeouts, error envelopes, and free-tier guards.

MCP server for Microsoft Fabric REST APIs that enables data engineers and analysts to manage Fabric components using AI assistants.

Enables LLM clients to encode, decode, and transform data using CyberChef operations via an MCP server that interfaces with the CyberChef API.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

Enables natural language management of Apache Airflow workflows, including DAG monitoring, task control, and configuration, via the Model Context Protocol.

A Model Context Protocol (MCP) server that provides a comprehensive interface to the Labellerr SDK for managing annotation projects, datasets, and monitoring operations through AI assistants like Claude Desktop and Cursor.

Exposes safe JSON contracts for validating and preparing datasets, running supervised fine-tuning, preference learning, RL, distillation, and evaluation, and managing checkpoints and exports through the Tinker SDK and Cookbook. It lets agents discover models and Hugging Face datasets, plan and execute training recipes, compare experiments, and export selected models.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.