Scans a local directory for table-like files (CSV, Parquet) and optionally includes subdirectories.
MIT
468,250 tools. Updated 2026-08-22 16:49
"Parsing and Unparsing CSV Files for AI Context Use" matching MCP tools:
- Validate data files by parsing JSON, checking CSV shape, and verifying SQLite integrity. Use as a smoke check to detect corruption early.MIT
- Saves Chronulus forecast data and explanations to CSV and TXT files for analysis and reference, with optional rescaling capabilities.PythonMIT
- Search repositories and receive AI-synthesized analysis of code. Streams intelligent summaries to explain matching files and deliver code context.MIT
- Initialize a complete workflow session by loading agents, skills, files, and libraries into the AI assistant's context.MIT
- Load CSV seed files into database tables to provide reference data for models and tests. Use state-based selection to only load changed seeds.MIT
Matching MCP Servers
- AlicenseNot gradedqualityAmaintenancePrivate knowledge base with Markdown pages and assets, exposed via MCP for agent access.12MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.1GPL 3.0
Matching MCP Connectors
CSV <-> JSON MCP.
Compact, citation-verifiable public web context for AI agents, paid per use with x402.
- Installs local multi-agent coordination files so AI agents, Xcode, and humans share the same project truth layer. Use once per project to set up .axint/agent, context, and coordination files.Apache 2.0
- List files and subcollections in any collection for a quick overview of available content. Explore the structure of digital scholarly editions without parsing document contents.MIT
- Detect your project's tech stack and regenerate AI context files from configuration. Use after framework changes or when context files become outdated to maintain accurate AI assistance.MIT
- Export SQL query results directly to CSV or JSONL files, handling large datasets without loading into context.MIT
- Load CSV files as seed data to create reference tables, test datasets, or static data for database models.MIT
- Retrieve and format all markdown files from a specified project directory to provide AI assistants with structured project context for enhanced task understanding and execution.MIT
- List all locally saved CSV datasets with file sizes and row counts to manage downloaded open data files.MIT
- Converts PDF, DOCX, XLSX, and CSV files into compact markdown before they enter the context window, reducing token usage by up to 98%.MIT
- List CSV lookup table files in Splunk and view their metadata, including name, owner, permissions, and last updated time. Use this to discover available lookup files for your searches.Apache 2.0
- Retrieve all Memory Bank files (product-context, active-context, progress, decision-log, system-patterns) as a single JSON object for quick context loading in AI assistants.MIT
- Upload CSV or text data to an Anaplan file, overwriting existing content. Compress large files for faster transfer.MIT
- Load all CSV files from a folder into a temporary SQLite database to enable data analysis and querying.MIT
- Reads an email and provides formatted context for an AI assistant to draft a reply. Use with email_reply to send.MIT
- Monitor a CSV file for new records appended since a cursor position, useful for tracking actively-written files.MIT