"Hugging: Exploration and Resources" matching MCP servers:

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

A simple MCP server that provides a calculator tool for basic arithmetic operations.

Enables AI agents to inspect any public domain’s web technology stack, email deliverability and DNS health (MX, SPF, DKIM, DMARC, MTA-STS, TLS-RPT, BIMI), and HTTPS security posture with typed JSON scores and remediation-ready findings, plus history, bulk checks, monitoring alerts, and reverse technology lookups.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

An MCP server that provides Hugging Face Hub API and Search endpoints through multiple transport protocols (STDIO, SSE, StreamableHTTP, and StreamableHTTPJson), enabling integration with AI model capabilities.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables LLMs and MCP clients to discover and use generated CRUD services through MCP tools and resources, exposing actions like create, update, delete, and read-only list/get access alongside REST endpoints.

Enables AI assistants to discover and invoke generated CRUD tools and read-only resources, letting them interact directly with REST-backed services built on Express, Mongoose, or Sequelize.

Enables LLMs and AI assistants to discover and use tools and resources for CRUD operations on generated services, providing direct interaction with the same data exposed by REST endpoints.

Enables LLMs to discover and invoke CRUD tools and read-only resources for generated services, allowing direct interaction with the same data exposed by the REST API.

Enables LLMs to discover and invoke generated API operations as MCP tools and resources, supporting create, update, list, and get-by-id actions over the same data exposed by the REST API.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

Enables LLMs to interact directly with generated REST services by discovering and invoking CRUD tools and reading exposed resources for list and get-by-id data.

It enables AI assistants to discover and invoke CRUD operations as MCP tools and read application data through MCP resources, allowing natural-language interaction with the generated backend.

It enables LLMs to interact with generated REST APIs by exposing CRUD operations as MCP tools and readable records as MCP resources. This lets AI clients discover and manage API data through the Model Context Protocol.

Enables LLMs to discover and invoke CRUD operations and read-only data resources for generated services through the Model Context Protocol, alongside traditional REST endpoints.

Enables AI assistants to discover and invoke generated CRUD actions as MCP tools and read-only data as MCP resources, so they can interact with REST APIs through a standard protocol.