50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.
Lets an AI agent pull the user's own Douyin creator-backend work data — plays, likes, comments, shares, saves, 5-second completion rate and more — into a locally accumulating CSV plus a daily overview, with tools for status checks, fetching, merging, and retrospective analysis. Access is read-only to the user's own account, needs no third-party dependencies, and keeps all data on the local machine.
A stdio MCP server exposing a validate_emails tool that lets agents screen email lists without sending mail or probing SMTP, checking syntax, DNS/MX records, disposable domains, role accounts, free providers, typo suggestions, and SPF/DMARC. Each address comes back with a valid/risky/invalid/unknown verdict plus machine-readable reason codes so agents can clean leads and signups before outreach or import.
Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.
MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.
Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.
Institutional-grade zero-lookahead Technical Analysis scanner with quantitative confluence scoring & native Model Context Protocol (MCP) server for AI trading agents.
It gives Claude Code, Cursor, and Codex structured workflows and an MCP
server for building data pipelines with dlt - covering REST API ingestion,
transformations, data quality, and exploration.
Enables users to convert structured data into Token-Oriented Object Notation (TOON) to reduce LLM token usage and costs by up to 70%. It provides tools for encoding, decoding, and analyzing data formats like JSON, CSV, and XML to optimize prompt efficiency.
Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.
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.
MCP server for Lakehouse42, enabling code-first tool discovery, hybrid search, document management, and Iceberg time-travel queries with optimized responses.
An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.
Bootstrap MCP server for future data exploration and querying across multiple databases, currently only provides a hello_world tool with no actual data connectivity.
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.