Sail is a project aiming to unify stream processing, batch processing, and compute - intensive (AI) workloads. It provides an alternative to Spark SQL and Spark DataFrame APIs and supports both standalone and distributed environments.

MaverickMCP is a personal stock analysis server based on FastMCP 2.0, providing professional level financial data analysis, technical indicator calculation, and investment portfolio optimization tools for MCP clients such as Claude Desktop. It comes pre-set with 520 S&P 500 stock data, supports multiple technical analysis strategies and parallel processing, and can run locally without complex authentication.

The Graphlit MCP Server is an integration tool that connects MCP clients with Graphlit services, supporting the ingestion, processing, and retrieval of multiple data sources.

Awesome MCP Servers is a comprehensive collection of Model Context Protocol (MCP) servers, covering 7,158 MCP servers divided into 33 categories, including AI integration, art and media, browser automation, cloud services, databases, developer tools, file systems, finance, gaming, hardware, healthcare, infrastructure, knowledge management, location maps, marketing, monitoring, multimedia processing, operating systems, project management, scientific research, security, social media, travel and transportation, utilities, and version control, etc.

flyto-core is a debuggable automation engine that provides complete execution tracking, arbitrary step replay, and status snapshot functions. It supports 412 modules covering 78 categories such as browser automation, data processing, and API integration, and can be used through multiple methods such as CLI, MCP server, and HTTP API.

Clippy is a macOS terminal clipboard tool that supports copying file references, GUI pasting, management of recently downloaded files, processing of pipeline data, and AI integration with the MCP server, improving work efficiency.

The ScrapeGraph MCP Server is a production - ready model context protocol server that provides seamless integration with the ScrapeGraph AI API, enabling language models to leverage advanced AI - driven web scraping capabilities.

The MCP server for Glide API, supporting versions v1 and v2, providing secure API interaction and data processing functions.

MarketScope AI is an intelligent healthcare market analysis platform that provides functions such as healthcare segment market analysis, product comparison, and sales data insights through AI and natural language processing technologies.

An MCP protocol server implementation for the k6 load testing tool, providing data reception and processing functions

The FHIR MCP Server is a medical data management server based on the FastMCP framework, providing a complete implementation of the Model Context Protocol (MCP) and supporting the interaction between LLM agents and FHIR-compatible backends. It provides standardized interfaces, supports comprehensive CRUD operations on FHIR resources, and implements intelligent document processing and semantic search through a series of tools.

The CSV Editor is an AI - driven MCP server that provides powerful CSV data processing capabilities for AI assistants, including data cleaning, transformation, analysis, and validation, and supports auto - save and history tracking.

The Eyevinn Open Source Cloud MCP Server provides web services such as databases, storage, and VOD processing pipelines based on open source technologies, avoiding vendor lock-in and supporting revenue sharing for creators.

Scanpy MCP is a natural language processing server designed for the single-cell RNA sequencing analysis software Scanpy, supporting operations such as data reading and writing, preprocessing, analysis, and visualization through natural language. It is suitable for researchers and proxy developers.

The Eyevinn Open Source Cloud MCP Server provides database, storage, and VOD processing services

This is a production-level medical agent server template based on the AOP protocol. It can deploy multiple professional medical agents as MCP tools, supporting the discovery and invocation of various medical analysis agents (such as laboratory data interpretation, ICD-10 coding, treatment plans, drug interactions, imaging triage, and clinical note summarization) through MCP clients, and providing functions such as queue management, dynamic discovery, and batch processing.

MCP-DBLP is a service based on the Model Context Protocol (MCP) that provides large language models with the ability to access the DBLP computer science literature database, including functions such as search, citation processing, and BibTeX export.

An MCP server for processing Building Information Modeling (BIM) files, providing functions for converting IFC files to Fragment format, loading Fragment files, and querying BIM data by category.

The MCP Server is an interaction system based on the Model Context Protocol standard, combining IPFS distributed storage and Claude AI processing capabilities to achieve efficient interaction between models, agents, and contextual data.

Snowflake MCP Service is a server that implements the Model Context Protocol (MCP), providing the ability for MCP-compatible clients to access Snowflake databases. It supports two authentication methods: password and key pair, and includes core functions such as connection management and query processing.

This is a collection of MCP servers focused on the medical field, covering various medical - related MCP service implementations such as PubMed literature retrieval, access to medical preprints, FHIR data interaction, DICOM medical image processing, protein structure analysis, medical computing tools, and integration of medical education resources.

This project is a document processing server based on the Model Context Protocol (MCP) standard. By building a vector database and an MCP interface, it enables AI assistants to access external document resources and break through the knowledge limitations of large language models. The project includes two major components: a document processing pipeline and an MCP server. It supports multiple embedding models and file formats and can be applied to scenarios such as querying the latest technical documents and understanding private code libraries.

The Yunxin MCP service provides a set of tools for large model processing of Yunxin IM/RTC functions and data, including message sending, historical query, data statistics, and real-time monitoring.

An MCP server that provides data retrieval and analysis services for the Ramp platform, implements ETL pipelines and in-memory SQLite database processing through the developer API, and supports multiple data loading and query tools.

The Dumpling AI MCP Server is a model context protocol server integrating multiple AI functions, providing capabilities such as data scraping, content processing, knowledge management, AI agents, and code execution.

A professional serial communication MCP server that provides AI assistants with comprehensive serial communication capabilities, supports embedded systems, IoT devices, and hardware debugging, and has cross - platform support and multiple data format processing functions.

SQLite MCP Server is an enterprise-level SQLite database enhancement tool that provides 73 dedicated tools, supporting advanced analysis, JSON operations, text processing, vector search, geospatial operations, and intelligent workflow automation. It has AI-native JSON operations and enhanced security.

The TSAP MCP Server is a text search and analysis processing system based on the Model Context Protocol (MCP), providing standardized interface services for code intelligence and text analysis. The project consists of three major components: core TSAP functions, tool APIs, and the MCP adaptation layer. It supports various functions such as text search, code analysis, and data processing, and can be seamlessly integrated with MCP clients such as Claude Desktop.

The Mapbox Developer MCP Server enables AI assistants to directly access Mapbox developer APIs, helping developers build map applications more efficiently. It supports functions such as style management, token management, document query, and geographic data processing.

A production-grade lead generation system based on MCP SDK and Crawl4AI, supporting multi-source data aggregation, intelligent caching, and efficient concurrent processing to achieve full lifecycle management from discovery to enrichment.

The MCP Document Indexer is a Python - based local document indexing and search server that uses the LanceDB vector database and a local LLM (through Ollama) to implement real - time monitoring, multi - format document processing, and semantic search, and provides tools for AI assistants such as Claude through the Model Context Protocol (MCP).

SQLGenius is an AI - based SQL assistant that converts user questions into SQL queries through natural language processing technology, supports BigQuery database operations, and provides interactive data visualization and schema exploration functions.

The Ntropy MCP server is a service that enriches bank data and provides a convenient interface call for LLM agents processing financial data through the Ntropy API.

The Nocodb MCP Server is a TypeScript - based service that supports interacting with Nocodb databases through the Model Context Protocol (MCP), enabling CRUD operations, file uploads, and bulk data processing.

The Dumpling AI MCP Server is a protocol server implementation that integrates multiple AI functions and data processing capabilities

A Python-based document processing and Retrieval Augmented Generation (RAG) server that uses the DuckDB database to store embedding vectors, supports multiple file format processing, and provides a Web interface and API.

A set of Python tool servers implementing the MCP protocol, providing function extensions such as YouTube data processing, Word document processing, and chart rendering for AI assistants.

A privacy - first document search server that runs entirely locally, providing semantic search functions for AI programming tools through the MCP protocol. No API keys or cloud services are required, and all data processing is completed on the user's computer.

This project is a BI chart MCP service implemented in Python for data visualization, including data loading, processing, and rendering modules.

A powerful JSON data processing tool that offers schema generation, intelligent filtering, and remote data support, specifically designed for LLM context optimization.