Latest MCP Servers

Read and write records in a Pinecone vector index via Model Context Protocol, enabling semantic search and document management for Claude Desktop.

Provides a collection of Model Context Protocol servers built with Quarkus, enabling rapid deployment of database access, JVM inspection, filesystem serving, JavaFX canvas, Kubernetes interaction, container management, and Wolfram Alpha search via simple JBang commands.

Provides an API to store and retrieve text passages based on semantic similarity, leveraging Ollama for embeddings and ChromaDB for vector storage and similarity search.

Enables MCP clients to interact with Monday.com boards, items, updates, and documents.

Extracts YouTube video metadata and transcripts via an MCP server, offering tool-based access, detailed logging, and robust error handling.

Enables comprehensive, well‑cited research reports by elaborating questions, generating sub‑questions, performing web searches, analyzing content, and formatting findings into structured artifacts.

Provides MCP endpoints that enable AI models to list buckets, retrieve file lists, upload and download files, generate download links, perform image scaling and rounding, and refresh or prefetch CDN resources on Qiniu cloud.

Pins third‑party dependencies—Docker base images and GitHub Actions—to immutable digests, ensuring reproducible builds and protecting against supply‑chain attacks.

Provides standardized access to CoinMarketCap data through a Model Context Protocol server, enabling retrieval of cryptocurrency market metrics, exchange information, OHLCV data, and related blockchain statistics.

Provides a STDIO MCP server that forwards requests to a Streamable HTTP MCP server, enabling any MCP client with STDIO support to communicate with Streamable HTTP back‑ends instantly.

Blazingly fast, asynchronous, and lightweight MCP server that handles filesystem operations efficiently. Starts read‑only by default, supports advanced glob pattern matching, and allows creation of nested directories, all compiled into a single binary with minimal resource footprint.

A versatile tool that enables interactive data exploration through prompts, CSV loading, and script execution.

Provides a standardized API to interact with multiple Kubernetes clusters simultaneously using multiple kubeconfig files.

Provides AWS CLI functionality via a Model Context Protocol server, enabling portable use across AI tools and editors.

Enables Claude Desktop and other MCP clients to access any OpenAI‑compatible chat completion service as a tool, forwarding queries to the configured provider.

Provides a TypeScript‑based MCP server that enables seamless interaction with ArangoDB through a set of tools for querying, inserting, updating, removing, backing up data, and managing collections.

Creates multiple query tools that connect to specific managed LlamaCloud indexes, exposing each as a searchable MCP tool.

A Python framework that enables seamless integration of Pydantic validation with large language models, providing type‑safe agent construction, dependency injection, and structured output handling.

Provides Deepseek model's chain‑of‑thought reasoning to MCP‑enabled AI clients, supporting both OpenAI API mode and local Ollama mode.

Enables AI assistants to retrieve and filter Intercom conversations and tickets using advanced search criteria, supporting date ranges, keywords, customer identifiers, and ticket status.

Provides a unified MCP endpoint that queries public SearXNG instances, parses HTML results, and returns them as a clean JSON array.

Provides secure access to Oura Ring health metrics via the Model Controller Protocol, enabling AI assistants to fetch, analyze, and visualize personal wellness data.

Enables searching and retrieving detailed entries from the Standard Korean Dictionary through an MCP API.

Provides AI assistants read/write capabilities for Microsoft OneNote notebooks, sections, and pages via the Model Context Protocol.

Interact with Hugging Face datasets via an MCP server, enabling browsing, searching, filtering, and analysis of public and private collections.

Provides vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and persistent storage for documents.

Interact with the arXiv API using natural language to retrieve article metadata, download PDFs, perform searches, and load full texts into large language model contexts.

Provides video generation and status checking via the json2video API for seamless integration with LLMs, agents, and other MCP‑compatible clients.

Provides an MCP server that exposes Redis operations as resources and tools for LLM integration, enabling caching, key‑value storage, list, hash, set, and Pub/Sub interactions with automatic reconnection handling.

Provides Unity Catalog Functions as MCP tools, enabling language models to list, retrieve, create, and delete catalog functions directly from a running server.

Extends the Model Context Protocol to serve any Python command‑line application, allowing CLI tools to be accessed programmatically through MCP.

Implementation of the Model Context Protocol for Oat++ that enables automatic generation of LLM‑compatible tools, prompts, and resources with transport options via STDIO or HTTP Server‑Sent Events.