"Browser Automation and Form Filling Tools" matching MCP servers:

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

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.

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

Enables local MCP-assisted processing of Access database tables, HTML5 advertising ZIP image assets, layered PDFs, and ONIX book-update requests through RapidAPI. It saves results in a selected workspace folder while requiring explicit consent for each processing call.

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.

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;

Exposes 20 read/write tools that let IDE and agent users search the interface catalog, build and validate flow-model JSON, import OpenAPI specs, run ETL tasks, and plan or revoke service permissions on RestCloud-compatible integration platforms. Writes default to dry-run and every call is written to a desensitized jsonl audit trail.

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 AI assistants to inspect and extract invoice metadata from PDFs, Word documents, Excel files, and images, then synchronize and enrich the extracted data into an Excel ledger.

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

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.

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

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.

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.

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.

Enables repair of malformed JSON strings into valid JSON for agent workflows by fixing common LLM formatting issues. Supports cleanup of code fences, smart quotes, unquoted keys, trailing commas, and missing brackets to ensure reliable data parsing.

Enables AI assistants to interact with SAP Datasphere for data exploration, querying, and administration via 49 tools.