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.
Provides AI tools with direct read access to the Built Online Podcast Command Center data, enabling validation, recommendations, and visibility of missing data without guessing.
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.
Open-source MCP server and notebook that finds Databricks cost waste (idle clusters, oversized warehouses, Delta tables needing OPTIMIZE/VACUUM) from system tables and proposes reviewable fixes. Read-only.
Enables looking up mobile phone numbers for a list of contacts by chaining your own Prospeo, Lusha, ContactOut, and FullEnrich keys until a provider returns a number. Returns one row per contact with the number in E.164 format, line type, country, a Do Not Call flag where reported, and the provider credits spent.
Enables AI agents to discover and access 800TB+ of public geospatial data from Source Cooperative, with tools for listing organizations, products, files, and fuzzy search.
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.
Enables finding and verifying work emails for contacts through a waterfall of provider keys, with per-provider cost attribution and verification after each finder.
This MCP server enables database migration between heterogeneous systems (Oracle, PostgreSQL, SQL Server, Netezza to PostgreSQL or SQL Server) through AI assistants by providing tools for command preview, execution, validation, and workflow suggestions.
Resolves messy company, customer, and vendor names across CRM, ERP, and ITSM systems to canonical records using fuzzy matching, preventing AI agents from updating or creating wrong or duplicate records.
A local MCP server for reviewing student housing form submissions, supporting listing, validation, duplicate detection, summarization, and data extraction with optional AI analysis.
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 users to clean and de-duplicate sales lead lists locally without API keys or network calls. It normalizes names, emails, phone numbers, and website domains, drops invalid emails, removes duplicate leads by email, and validates email formatting.
A Python MCP server for deterministic fuzzy text matching using RapidFuzz. It enables text normalization, string comparison, best-match ranking, duplicate grouping, and match explanation via configurable profiles and strategies.
Provides access to Chinese A-share market financial data, including historical K-line, real-time quotes, financial statements, shareholder information, and technical indicators, via MCP protocol.
Enables automatic conversation summarization by typing -sun command, which analyzes the current chat session and saves structured summaries as .mdc files with key insights, outcomes, and next steps.
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.
Enables generation of various chart types (bar, line, pie, radar, etc.) using QuickChart.io and Chart.js configurations, with options to generate chart URLs or download images locally.
A fail-closed MCP verification layer for DFT-to-MLIP workflows, gating Quantum ESPRESSO data ingestion, MACE/RuNNer dry-run command plans, model comparison, and reference validation behind scientific, software, and numerical checks with explicit PASS/WARN/FAIL/QUARANTINE/NOT_RUN statuses.
Enables LLM agents to interact with the MOSTLY AI Platform for generating synthetic data, including training generators, managing data connectors, executing queries, and generating synthetic datasets with OAuth 2.1 authentication.
Exposes ERP data (production orders, inventory, BOM, customers) to any MCP client through a backend-neutral interface, with a mock backend for testing.
Enables AI agents to import and refresh product feeds, edit products, write rules, run optimization and audits, connect ad channels, set performance labels, and create product ad creatives.
Enables users to log AI tool activity without conversation text and contribute back only user-approved, small-cell-suppressed counts through a local MCP interface.
Enables AI clients to serve as a personal career analyst by searching, matching, and explaining job recommendations, managing job applications, and syncing public job boards through standardized MCP tools.