Data Analytics MCP Repositories

Integrate various tools for enhanced development workflows, including managing emails, calendars, and research tasks. It provides functionalities for development tools, data fetching, and leveraging academic resources.

Integrates real-time web research capabilities into workflows by enabling Google search, webpage content extraction, research session tracking, and screenshot capture.

Conduct comprehensive research on cryptocurrency tokens by aggregating data from multiple trusted sources. Manage and store research content, track progress through research stages, and generate detailed reports.

Interact with Sentry's API to retrieve and analyze error data, manage projects, and monitor application performance. Integrate Sentry's capabilities directly into applications for enhanced error tracking and project management.

Facilitates interaction with Databricks workspaces via a Model Context Protocol interface, enabling users to list catalogs, schemas, tables, and SQL warehouses, as well as execute SQL queries.

Integrates real-time web search and intelligent data extraction to enhance AI assistants with up-to-date information and sophisticated filtering capabilities. Supports domain-specific data retrieval and processing features for improved AI workflows.

Clone local git repositories, process branches and files, generate embeddings for code chunks, and perform semantic searches over code. Utilize local repositories for efficient code context retrieval and improve development workflows.

The ActivityWatch MCP Server allows AI models to access and analyze your time tracking data from ActivityWatch. This server makes it easy to manage and retrieve insights from your productivity information.

Fetch and analyze Reddit content, including hot threads and detailed posts with comments from any subreddit. Supports various post types such as text, link, and gallery to provide comprehensive insights.

Explore and analyze RDF data with a conversational interface, enabling execution of SPARQL queries in both local and endpoint modes for insights from knowledge graphs.

Extracts key-value pairs from noisy or unstructured text in multiple languages, ensuring type-safe outputs in JSON, YAML, or TOML formats. Utilizes advanced LLMs and pydantic for data structuring and validation, supporting languages like Japanese, English, and Chinese.

Integrates with the IMF data API for accessing and processing economic data, enabling users to query datasets, retrieve time series data, and list available indicators and countries.

Facilitates structured problem-solving and decision-making by breaking down complex issues into manageable stages, while tracking progress and categorizing thoughts for better organization. Dynamically adapts the thinking process as new insights emerge and generates comprehensive summaries of the problem-solving journey.

Enable interaction with Salesforce data by executing SOQL queries, retrieving metadata, and managing Salesforce records through a standardized MCP interface.

A drag-and-drop machine learning platform that utilizes Apache Spark for big data computation, enabling users to perform machine learning tasks without cloud services. It offers an intuitive interface for rapid setup and execution of data processing workflows.

Collect user account information from various social networks and analyze URLs to gather public data, enhancing research capabilities for OSINT investigations.

Enables interaction with Trino's distributed SQL query engine for executing complex SQL queries and discovering data catalogs. Facilitates data analytics capabilities through a high-performance MCP server built in Go.

Connect to the Wolfram Alpha API for computational knowledge and query processing. This server enables users to obtain answers to mathematical, scientific, and general knowledge queries through an API interface.

Fetches comments from GitHub Pull Requests, including details about file paths and replies, utilizing the GitHub API for structured data access.

Execute XPath queries on XML and HTML content, fetching and querying data from URLs or local files. Return structured results to enhance applications with powerful XML data manipulation capabilities.

Fetches and stores documentation in a vector database for semantic search and retrieval, enhancing LLM capabilities with relevant documentation context. Supports adding documentation from URLs or local files and querying with natural language.

Access Fathom Analytics data through an AI assistant, enabling the retrieval of account details, site management, and report generation with real-time visitor tracking.

Enables interaction with the open World Bank data API to provide access to various indicators and analysis for different countries.

Analyzes user search keywords to reveal intent and provides insights for enhancing SEO strategies. Delivers possible categories, reasoning, and related references to improve search effectiveness.

Extract data from Excel files in structured JSON format, allowing access to all sheets or specific sheets by name or index. Handles data type conversions and manages empty cells efficiently.

Enables LLMs to read, search, and analyze code files while providing advanced caching and real-time file watching capabilities. Facilitates file operations and code analysis to improve development workflows and quality metrics.

Diffs and patches JavaScript objects and arrays, enabling change tracking and state reversion through a simple API.

Provides structured access to cryptocurrency whitepapers for searching, loading, and querying detailed content, enabling efficient analysis of tokenomics and project-specific insights.

Extracts video metadata and captions from YouTube videos, converting them into customizable markdown formats. Supports multiple languages and offers search functionality within captions.

Search documents using private data while enhancing result quality through grounding. Integrates multiple Vertex AI data stores to improve search capabilities with the support of Gemini.