"Chrome DevTools - Browser Developer Tools & Debugging Resources" matching MCP servers:

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

An experimental multimodal AI data infrastructure that allows users to manage tables, run local AI analysis like object detection, and automate data workflows. It includes an interactive Python REPL and introspection tools for exploring Pixeltable functions directly through Claude or Cursor.

MCP server for Grubhub Data Platform operations, providing 40+ tools across 18 service categories for data platform management, observability, analytics, and collaboration.

Enables validating IFC models against IDS requirements with coverage reporting, auditing LOD by project stage, and extracting quantity take-offs, including combined audit summaries and full BIM health checks. It exposes these capabilities as MCP tools for Claude Desktop, producing Excel, HTML, and BCF reports.

Enables validating CSV structure, checking simple schemas, converting between CSV and JSON, sampling rows, and finding duplicate keys on local files. All processing stays local, so no user data is ever uploaded.

Read-only MCP tools for TROCCO API, enabling workflow and BigQuery datamart audit information retrieval.

Enables AI agents to interact with local SQLite databases with full CRUD, schema introspection, foreign key relations, generated columns, and multi-format import/export (CSV, JSON, XLSX) through natural language.

Enables high-precision detection, anonymization, encryption and decryption of personally identifiable information (PII) in text using GPT-4o-based detection and advanced cryptographic methods. Supports both deterministic encryption for searchable data and format-preserving encryption for structured identifiers.

An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

An MCP server that provides tools for JSON validation, diffing, and transformation operations such as flattening and renaming. It also enables data format conversion between JSON, CSV, and YAML to streamline data processing for AI agents.

CSV Tools AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Free remote MCP server for GIS/ArcGIS Online automation — coordinate/EPSG conversion, GeoJSON validation and geometry operations, ArcGIS FeatureServer inspection (feature count/query, schema, health check), and Shapefile/KML/GPX/WKT format conversion. Works with public ArcGIS layers without a token;

Enables LLMs and agents to interact with relational databases (SQL Server, MySQL, PostgreSQL) through MCP tools. Supports executing queries, inserting records, listing tables, and exposing database schemas with secure credential management.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.

An MCP server that provides access to the LinkedIn Bulk Data Scraper API and various utility tools for data extraction and processing.

Enables managing the full data quality lifecycle through Claude Desktop, including data exploration, profiling, validation, duplicate detection, reconciliation, workflows, schedules, and execution monitoring.

Enables cross-database and domestic-database migration analysis by checking type mappings, dialect gaps, NULL and charset/collation semantics, object parity, SQL translation, consistency verification with checksums and sampling, effort estimation, and migration planning/reporting.

Enables the analysis of DBT manifests with automatic schema version detection and lineage tracking, allowing users to query model dependencies, access compiled code, and get detailed model information.

Enables teams to structure metric definitions, compare semantic differences, detect JOIN fanout and drift, reconcile mismatched numbers layer by layer, and persist metric contracts as YAML.