"Cómo ver errores y advertencias en Visual Studio Code" matching MCP servers:

MCP server that enables Claude to control Altair AI Studio for data mining and machine learning tasks, including data import, cleaning, transformation, model training, clustering, association rules, and executing saved processes.

Enables AI hosts to design and simulate complex adaptive systems, including managing agent types, running simulations, and analyzing emergent behavior, feedback loops, and sensitivities.

Python-first MCP server for CST Studio Suite (2024–2026) that lets AI assistants drive CST from Windows: open projects, build geometry, set materials and ports, run solvers, read S-parameters and farfield metrics, and generate design reports.

Enables AI agents to drive IBM SPSS Statistics for statistical analysis and publication-quality chart generation through natural language, returning structured results and ensuring safe execution.

MCP server for BIOVIA Materials Studio 2023 on Windows, providing controlled preparation of Forcite and CASTEP inputs, model building, and LAMMPS/VMD pre-processing with reproducible, auditable workflows and strict scientific boundaries.

MCP server for the DAG Studio causal-inference engine, enabling AI agents to construct, analyze, and validate causal directed acyclic graphs (DAGs) through tools for analysis, data simulation, and code generation.

An agent-based tool that provides web search and advanced research capabilities including document analysis, image description, and YouTube transcript retrieval.

Enables AI to search, filter, and process CNKI academic literature through natural language, including structured search, metadata retrieval, full-text reading, citation export, and PDF/CAJ download.

Provides professional market data access via DataBento API, including real-time futures quotes, historical timeseries, batch downloads, symbol resolution, metadata discovery, and reference data.

Provides tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.

Enables MCP clients to fetch live football odds and team form, and flag matches where the market price diverges from a simple form-based estimate.

Enables AI clients to query ContentRadar data and write low-risk content using natural language, with 15 tools for monitoring, analysis, and content management.

Enables human-coordinated multi-agent workflows for Earth-observation research, Cube Chess 512 self-play benchmarking, and reversible visual QA through WebMCP tools with verification and approval gates.

Enables searching and discovering machine learning papers, state-of-the-art benchmarks, tasks, datasets, methods, and leaderboards from Papers with Code. Supports mapping papers to their benchmark results and browsing evaluation tables.

Bilingual (EN/ES) AI-writing detection that shows the evidence instead of a percentage: named tells with line and column, hidden-character inspection, and citation cross-checking against a document's own bibliography. Seven of its nine tools run entirely locally and never touch the network.

Enables AI agents to edit LaTeX documents with live PDF preview, commenting, and visual editing via the Model Context Protocol.

Enables LLMs to generate visual summary reports from CSV datasets using MCP Resources, Tools, and Prompts, without exposing raw data to the model.

Fast, local PDF parsing as an MCP server with text extraction, bounding boxes, OCR, and visual citations. No cloud or API key required.

Installable MCP server for EU legal research with verifiable CELEX citations from the EUR-Lex corpus (DE/EN/FR).

A professional literature search tool built on FastMCP framework that enables AI assistants to search academic literature from Europe PMC, retrieve article details, and analyze journal quality with seamless integration into Claude Desktop and Cherry Studio.