"Discover" matching MCP servers:

MCP server registry and marketplace that enables dynamic discovery, installation, and activation of tools at runtime, allowing AI agents to use new tools without restarting.

Enables searching and inspecting GitHub repositories, including topic and trending searches, repo overviews, file browsing, commit history, branches, and side-by-side repo comparisons.

Discovers, inspects, and executes requests against OpenAPI or Swagger APIs directly from documentation URLs or specification files. It enables users to trace parameter usage across an API and perform authenticated HTTP requests through a structured toolset.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Enables scanning Java/Maven projects to generate TOGAF-standard architecture deliverables (Excel and PPTX) via natural language commands.

An MCP server that provides access to Google's API Discovery Service, allowing agents to discover and interact with Google APIs through natural language commands.

A meta-MCP server that discovers and explores other MCP servers using progressive disclosure patterns to reduce token usage by up to 99%.

Enables LLMs to discover, read, and edit tables in HTML/Markdown documents by converting messy collapsed HTML into clean pipe format and writing back with version-checked, surgical cell, row, and column operations.

Enables LLMs to discover, understand, and generate Teal R Shiny applications for clinical trial data analysis.

Public read-only registry for Codex-compatible animated companion packs. Search approved pets, fetch install instructions, generate badges and embed cards, and discover the pet request flow via Streamable HTTP MCP.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI to dynamically discover and invoke any Cin7 Core API endpoint using three generic tools (list, describe, invoke) plus a bug-report tool, covering the entire API surface without predefined endpoints.

Enables AI assistants to discover, install, configure, and manage MCP servers through natural language conversation, automating tedious manual setup across multiple clients.

An MCP server for SonarQube that enables LLM agents to discover projects, analyze code quality metrics, check Quality Gate status, search issues with filters, and rank projects by worst-performing metrics. It provides read-only, safe access to SonarQube instances with structured outputs and error handling.

Read-only MCP server for GenieLocker that exposes tools for service status, commercial inventory, live quotes, recipe search, and credit pricing, without enabling purchases or model inference.

MCP server for the ReactUse library. Exposes 110+ React Hook signatures, examples, and API metadata so AI coding assistants can discover and use any hook from @reactuses/core directly.

MCP server for appCN - discover, search, install, and correctly use copy-paste React Native / Expo UI components (including an AI-native collection) from the live registry

Enables AI agents to discover, inspect, and call SAP RFC-enabled function modules (BAPIs/RFCs) with configurable read/write policies, transaction support, audit logging, and ABAP source retrieval.

Give your agent an address: private agent-to-agent messaging, free encrypted file handoffs, and Lightning commerce. Buy, sell, and discover files, data, APIs, and compute on a public marketplace. Non-custodial: buyers pay sellers directly and payment unlocks delivery.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.