Latest MCP Servers

Enables AI agents to invoke Liveblocks REST API endpoints for creating, modifying, and deleting rooms, threads, comments, notifications, and provides read‑only access to Storage and Yjs data structures.

Enables LLMs and other intelligent agents to configure, monitor, and manage Litmus Edge devices through real‑time Model Context Protocol communication.

Integrates the LINE Messaging API with a Model Context Protocol server, enabling AI agents to send text, flex, broadcast messages, retrieve user profiles, and manage rich menus on a LINE Official Account.

Provides a Model Context Protocol server that enables AI clients to read and modify LaunchDarkly feature flags and AI Configs directly from their workflows.

Provides AI agents with real‑time production context—including logs, metrics, traces, and alerts—through a Model Context Protocol server, enabling automatic code fixing and faster debugging.

Access and manage Langfuse prompts through the Model Context Protocol, enabling prompt discovery, retrieval, and compilation via MCP endpoints and compatible tool commands.

Provides a lightweight side‑car that translates MCP tool calls into authenticated requests to Landing AI’s VisionAgent REST APIs, returning JSON responses and visual outputs for computer‑vision tasks.

Provides a semantic search API for macroeconomic data, enabling AI agents and quantitative research tools to retrieve relevant economic indicators via MCP calls.

Provides programmatic access to Kuzu graph databases, enabling language models to retrieve schema details and run Cypher queries directly against the database.

Enables exploration of KurrentDB data by reading, writing, and creating projections through a simple MCP server interface.

Enables integration of Knock's notification and management APIs into AI agent frameworks and Model Context Protocol clients, supplying ready‑made tools for OpenAI, Vercel AI SDK, LangChain, and custom MCP servers.

A bridge that connects Keboola projects with AI agents, exposing storage, component configurations, SQL transformations, job execution, workflow orchestration, and Data Apps through the Model Context Protocol.

Provides web search and video summarization capabilities through the Model Context Protocol, enabling AI assistants like Claude to perform queries and summarizations.

Provides LLMs with the ability to execute network measurement commands such as ping, traceroute, DNS, MTR, and HTTP across a global set of probes.

Provides repository management, build tracking, runtime monitoring, security scanning, and package catalog capabilities for the JFrog Platform via Model Context Protocol.

Run AI-generated Python code securely in persistent, stateful sandboxes that can stay active indefinitely.

Provides AI-powered project management capabilities via a Model Context Protocol server, allowing assistants to create, list, update, and delete tasks and documents in Dart without directly handling the underlying API.

Provides detailed geolocation information for IPv4 and IPv6 addresses using the IP2Location.io API.

Extracts text and performs OCR on images, PDFs, and Microsoft Office documents, converts documents to Markdown, and retrieves structured key information in JSON format.

Enables Make scenarios to be invoked as tools by AI assistants, handling parameter parsing and returning structured JSON results.

Provides actions for connected integrations on Integration.app, exposing tools through Model Context Protocol endpoints for static and dynamic usage.

Provides RAG‑powered retrieval of product documentation and content through a Model Context Protocol (MCP) endpoint.

Provides a Model Context Protocol (MCP) server that exposes Quickchat AI agents to any compatible AI application.

Provides tools to scrape, extract structured data, crawl webpages, and access general‑purpose browser agents such as OpenAI CUA, Anthropic Claude Computer Use, and lightweight Browser Use via a Model Context Protocol server.

Integrates the Hunter API with any LLM provider supporting the MCP protocol, enabling natural‑language access to B2B people and company data.

Enables LLMs to query and analyze Honeycomb observability data across multiple environments via the Model Context Protocol, providing real‑time insights into datasets, SLOs, triggers, and more.

Provides a Model Context Protocol bridge that connects AI assistants directly to the HiveFlow automation platform, enabling AI‑driven creation, execution, and management of automation flows via standard tool calls.

Enables large language models to manage and operate Heroku platform resources directly through the Heroku CLI, exposing a set of tools for app, dyno, add‑on, pipeline, database, and team operations.

Provides integration with Terraform Registry APIs, enabling automation and interaction for Infrastructure as Code development via Model Context Protocol.

Enables AI models to query and manipulate GROWI wiki content, providing page search, creation, tagging, comments, revisions, and share‑link management through the Model Context Protocol.