Top MCP Servers

Provides integration between Linear's issue tracking system and the Model Context Protocol, enabling LLMs to create, update, search, and comment on Linear issues via MCP tools.

Provides a local‑first, persistent memory layer for AI agents via the Model Context Protocol, consolidating session history, codebase indexing, and concept graphs in a SQLite store.

Provides Microsoft Teams integration via the Model Context Protocol, enabling reading, creating, replying to messages and mentioning members.

Offers a comprehensive suite of geospatial APIs and tools for developers and AI agents, enabling geocoding, reverse geocoding, POI search, route planning, weather, traffic, IP location, and real‑time traffic queries via standardized MCP interfaces.

Enables natural‑language interaction with KiCad projects through a Model Context Protocol (MCP) server, providing project management, design analysis, netlist extraction, BOM generation, DRC execution, PCB visualization, and circuit pattern recognition.

Provides AI assistants with full Xcode integration, enabling project creation, file manipulation, building, testing, CocoaPods and Swift Package Manager handling, and iOS simulator control.

Deploy HTML, folders, or zip archives to EdgeOne Pages and instantly obtain a public URL for fast edge delivery.

Deploy applications to Google Cloud Run via MCP, enabling AI agents, CLI extensions, and IDE integrations to perform deployments, list services, retrieve logs, and manage GCP projects.

Provides metacognitive sanity checks for autonomous AI agents, interrupting pattern inertia and preventing reasoning lock‑in through adaptive Critical Path Interrupts.

Enables SQL analytics on DuckDB and MotherDuck databases via a Model Context Protocol server, allowing AI assistants and IDEs to query data directly.

Interact with Twitter to post tweets and search tweets programmatically via an MCP server.

Offers an MCP server exposing Chroma's vector database capabilities for LLM applications, supporting collection and document management, multiple embedding functions, and flexible client types such as in‑memory, persistent, HTTP, and cloud.

Facilitates interactive communication between LLMs and users on the local machine, offering tools for user input, OS notifications, and persistent command‑line chat sessions.

Add code interpreting capabilities to Claude Desktop via the E2B Sandbox, available in JavaScript and Python editions.

Provides a secure, efficient, and personalized local AI chat experience with multi‑session management, markdown rendering, and extensible tool integration via MCP.

Provides a secure, unified endpoint for routing all MCP traffic, enforcing RBAC, policies, and full observability while supporting deployment on Docker, Kubernetes, Bun, or Node.

Provides advanced sequential thinking capabilities via a multi‑agent system, exposing a `sequentialthinking` MCP tool that orchestrates six specialized agents to analyze, research, and synthesize user thoughts.

Provides an infinite canvas for learning where any selected text can be queried and the answer appears as a fully‑rendered child document, working with Claude Code, Codex, or any MCP‑compatible agent.

Provides a secure sandbox environment for executing code within Docker containers, enabling AI applications to run untrusted code safely.

Inject relevant code and text from a project into Large Language Model chat interfaces via the clipboard or Model Context Protocol, using smart file selection based on .gitignore patterns and rule‑based customization.

Orchestrates multiple AI coding agents to collaboratively generate, test, and merge code based on a single goal, delivering deterministic execution, git worktree isolation, per‑agent credential scoping, and an HMAC‑chained audit trail.

A Model Context Protocol server that proxies DeepSeek's language models, enabling seamless integration with MCP‑compatible applications.

Enables large language models to control iOS simulators through natural language commands, offering full lifecycle management, app handling, UI interaction, debugging, and advanced simulation features.

Enables invocation of Dify workflows through Model Context Protocol, allowing tools to call Dify’s capabilities from any MCP‑compatible client.

Fast cross‑platform file searching leveraging the Everything SDK on Windows, Spotlight on macOS, and locate/plocate on Linux.

Provides a standardized interface for AI models to retrieve performance data, visualize creatives, and manage Meta advertising campaigns across Facebook, Instagram, and other Meta platforms.

Enables AI agents to query large‑context language models with collections of files that exceed the agent’s own context window.

Enables LLMs to interact with MongoDB databases via a standardized interface, offering schema inspection, query execution, aggregation, and write capabilities, with optional read‑only mode and smart ObjectId handling.

Control Neovim via Model Context Protocol using the official neovim/node-client library, delivering lightweight AI‑assisted code and text editing capabilities.

Secure Model Context Protocol server that enables command‑line interactions on Windows, supporting PowerShell, CMD, Git Bash and remote SSH operations.

A Python-native library that replicates Stata and R econometrics workflows, providing unified APIs, structured result objects, validation metadata, and MCP server integration for causal inference and applied statistics.

Provides a Node.js server that implements the Model Context Protocol to expose Mapbox geospatial APIs such as geocoding, POI search, routing, travel‑time matrix, isochrones, and static map images for AI agents and applications.