"Methods to Extract Data from Files" matching MCP servers:

Enables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.

Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.

Provides deterministic, schema-driven structured data extraction from PDF documents via regex/heuristic matching, enabling repeatable, inspectable, and cost-free field extraction without LLM API calls.

Enables AI agents to search and query the public DOJ Epstein Files release across 20 databases, resolve EFTA numbers to official DOJ PDFs, and cross-check viral claims against a fact-checked registry.

FastMCP server for PDF text extraction and metadata retrieval, providing structured JSON output for pages, metadata, and specific page ranges.

An educational MCP server that wraps the Materials Project API, exposing tools to search chemical systems, get material summaries, find semiconductors by band gap, and retrieve crystal structure facts.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

MCP server for the loc8n Geographic Data API. Exposes U.S. demographics, housing, mortgage, migration, employment, and geographic data as tools.

Enables loading and statistical analysis of .xlsx and .csv files with visualization capabilities using matplotlib and plotly to generate various graphs and charts.

An MCP server for dataset exploration and analysis, enabling LLM clients to perform summary, correlation, distribution, missing value analysis, data cleaning, and statistical tests directly on CSV files.

Exposes data query and auto-insights (anomaly detection) as MCP tools. Enables AI agents to query metrics, list columns, and get data insights directly from pandas.

Enables natural language search and discovery of open-access scientific datasets through the EOSC Data Commons OpenSearch service. Provides tools to search datasets and retrieve file metadata using LLM-assisted queries.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Enables scientific data introspection and visualization of VTK datasets with format-adaptive metadata extraction and interactive 3D visualization through MCP tools.

Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.

MCP server providing AI assistants with live access to 89 curated US workforce and labor market data sources, including BLS, FRED, Census, O*NET, DOL, SEC EDGAR, and real-time signals from Indeed and ADP.

An MCP server that lets AI assistants discover and retrieve official statistics from SDMX services, returning actual data observations rather than just query URLs.

Enables read-only access to public U.S. healthcare market-intelligence datasets, including catalogs, schemas, metadata, checksums, and artifact URLs. It supports CMOs, analysts, researchers, and AI agents in discovering and consuming governed market observations without patient-level data.