Jinni is an efficient tool for providing project context to large language models. It overcomes the limitations of reading files one by one by integrating relevant files and their metadata.

The arXiv MCP Server is a service based on the Model Context Protocol (MCP) that allows users to interact with the arXiv API using natural language, enabling functions such as retrieving academic article metadata, downloading PDF files, searching the database, and loading articles into the context of a large - language model (LLM).

The Meta Prompt MCP project simulates a multi - agent collaboration system through a single language model, realizing task decomposition and expert consultation functions, and simplifying the process of solving complex problems.

The PubMed MCP Server is an interface service based on the Model Context Protocol, providing comprehensive access to the PubMed biomedical literature database for AI agents and research tools. It supports functions such as literature search, metadata acquisition, citation analysis, research plan generation, and data visualization, and is efficiently integrated through the NCBI E - utilities API.

This project is an MCP server for the Metasploit framework, providing a bridge between large - language models (such as Claude) and the Metasploit penetration testing platform, and supporting the control of complex security testing workflows through a natural language interface.

The Kaltura MCP server is a service that implements the Model Context Protocol (MCP), providing AI models with standardized interaction capabilities with the Kaltura media management system, including media upload, metadata management, classification, and user management.

A model context protocol server based on LanceDB, providing functions such as vector storage, similarity search, and metadata management

OpenManus is an open-source project that allows users to realize various ideas without an invitation code. It was built by members of the MetaGPT team in 3 hours. It provides a simple implementation that allows users to create their own intelligent agents and supports multiple languages and configurations. The project welcomes suggestions, contributions, and feedback. Future plans include better planning, real-time demonstrations, playback functions, RL fine-tuning models, and comprehensive benchmarking.

Meta Ads MCP is a server based on the Model Context Protocol, used to interact with the Meta Advertising API through a standardized interface, enabling AI models to access, analyze, and manage Meta advertising campaigns, including obtaining performance data, visualizing advertising creativity, and providing strategic suggestions.

dicom-mcp is a DICOM-based model context protocol server that provides tools for large language models to query and interact with medical imaging metadata. It supports the retrieval of patient information, examinations, series, and instances, as well as the extraction of text from DICOM-encapsulated PDFs.

SearXNG MCP is a model context protocol server based on the SearXNG privacy-protecting metasearch engine, providing web search functionality for AI assistants. It supports zero-configuration use of public instances or connection to private instances, with features such as customizable search parameters, multi-search engine support, and privacy-first.

A Model Context Protocol (MCP) server that connects to the Domo API, providing dataset metadata query and SQL execution functions.

The Metabase AI assistant is an AI-driven tool that connects Claude Desktop/Code with Metabase and PostgreSQL databases through the Model Context Protocol (MCP), supporting natural language to generate SQL queries, create data models, and dashboards.

Google Scholar MCP Server is an interface service that provides AI assistants with access to academic papers on Google Scholar through the Model Context Protocol (MCP). It supports keyword search, advanced retrieval, and author information query functions to help AI models retrieve academic paper metadata.

A DataHub server implementing the Model Context Protocol, enabling AI agents to query metadata and context in the data ecosystem.

This is a server based on the Model Context Protocol (MCP) for executing SQL queries through the Databricks Statement Execution API, supporting complex task iteration and Unity Catalog metadata integration.

The Meta API MCP Server is a multi - API gateway server that connects various APIs with large - language models (such as Claude, GPT, etc.) through the Model Context Protocol (MCP), enabling AI assistants to directly interact with APIs and access real data sources. It supports quickly adding APIs from JSON configuration files or Postman collections, and provides comprehensive support for HTTP methods and multiple authentication methods.

A Wikidata API service implementation based on the Model Context Protocol, providing entity/property search, metadata extraction, and SPARQL query functions.

The Python Alfresco MCP Server is an Alfresco Content Services Model Context Protocol server built on the FastMCP 2.0 framework. It provides 15 tools such as full - text search, document management, and metadata operations, supports multiple transport protocols such as STDIO/HTTP/SSE, and is suitable for both Alfresco Community Edition and Enterprise Edition.

The PubMed MCP Server is a bridging service that provides AI assistants with access to the PubMed biomedical literature library via the Model Context Protocol (MCP), supporting literature search, metadata acquisition, and in - depth analysis functions.

DICOM-MCP is a DICOM server interaction tool based on the Model Context Protocol, supporting LLM access and analysis of medical imaging metadata.

The Sci-Hub MCP service is a bridge connecting AI assistants with Sci-Hub's academic resources, providing functions such as paper search, metadata acquisition, and PDF download through the Model Context Protocol.

The Blockscout MCP Server is an open - source service based on the Model Context Protocol (MCP), aiming to provide structured blockchain data access for AI agents, IDEs, and automation tools. It encapsulates the Blockscout API, supports multi - chain queries, including balances, tokens, NFTs, and contract metadata, and enables tools such as Claude and Cursor to analyze and utilize this data through context - aware APIs.

The Xano MCP Server is a server based on the Model Context Protocol, used to interact with the Xano metadata API and provide database management tools for AI assistants.

Agentify Components is a framework for adding semantic metadata to React components, enabling AI systems and automation tools to understand component functions. It adds standardized descriptions to components through decorators and generates MCP server configurations to enable interaction between components and AI models.

MetaTrader MCP Server is a Model Context Protocol server built on Python, aiming to achieve automated trading on the MetaTrader platform through AI large language models (LLMs). It supports integration with LLM tools such as Claude Desktop and Open WebUI and provides an HTTP server interface.

This project is an MCP server designed for the Metasploit Framework, providing an integrated interface between large language models and the penetration testing platform, and supporting the control of complex security testing processes through natural language.

The AIStor MCP server is a service based on the Model Context Protocol (MCP) for interacting with AIStor object storage. It supports various operations, including reading, writing, deleting, and management functions, such as listing buckets and objects, getting metadata, creating presigned URLs, and using AI to describe object content. It has flexible configuration and can enable operations at different permission levels through flags.

The medRxiv MCP Server is a bridge tool connecting AI assistants and the medRxiv preprint library, enabling functions such as searching for preprints, retrieving metadata, and accessing content in the field of health science through the Model Context Protocol (MCP). It supports local storage and paper analysis prompts.

A GitHub repository creation tool based on the Model Context Protocol (MCP) that provides the functions of automatically analyzing local code repositories, generating metadata, and creating well-configured GitHub repositories, and supports integration with AI tools such as Copilot.

The WatchBase MCP Server is a middleware service that provides access to the WatchBase data API for querying watch metadata, including brand, collection, model, technical parameters, and other information.

The Salesforce MCP Server is an implementation of a model context protocol server that interacts with Salesforce via the REST API. It uses the jsforce library and supports SOQL queries, metadata retrieval, and record operations.

The Crossref MCP Server is a bridge service that connects AI assistants with the Crossref academic database through the Model Context Protocol (MCP), supporting the search for papers, acquisition of metadata, and information on journals and funding agencies by DOI, title, or keywords.

A Python-based Model Context Protocol (MCP) server with a file system backend that provides functions such as note-taking, file operations, directory management, search, compression, and metadata retrieval.

The Kleros MCP Server is a multi-chain model context protocol service that provides comprehensive retrieval of Kleros court dispute data, including meta-evidence and evidence submissions, and supports the Ethereum mainnet and the Gnosis chain.

The Unpaywall MCP server is a tool server based on the model context protocol, providing functions such as obtaining academic paper metadata via DOI, searching for article titles, obtaining open-access full-text links, and downloading and extracting PDF text.

This project implements a server based on the Model Context Protocol (MCP) to provide metadata information of Rust Cargo projects, including package information, dependencies, build targets, etc.

PG-MCP is a model context protocol server designed for PostgreSQL databases. It provides APIs for AI agents to connect to, query, and understand databases, and supports multiple database connections, rich metadata extraction, and query analysis functions.

The PowerPlatform MCP Server is a tool that provides intelligent access to PowerPlatform/Dataverse entities and records, supporting functions such as metadata exploration, advanced queries, relationship mapping, and AI-assisted modeling.

A Salesforce REST API interaction server based on the Model Context Protocol, providing functions such as SOQL query, metadata retrieval, and record creation, update, and deletion. It supports quick installation and deployment via Smithery.