MCP server directory

LLMs rely on outdated or generic information about the libraries you use. You get: - ❌ Code examples are outdated and based on year-old training data - ❌ Hallucinated APIs that don't even exist - ❌ Generic answers for old package versions Context7 pulls up-to-date, version-specific documentation and code examples straight from the source — and places them directly into your prompt. Context7 fetches up-to-date code examples and documentation right into your LLM's context. No tab-switching, no hallucinated APIs that don't exist, no outdated code generation.

5 tools · Fetch current docs, Get real code examples

Chrome DevTools for agents (chrome-devtools-mcp) lets your coding agent (such as Antigravity, Claude, Cursor or Copilot) control and inspect a live Chrome browser. It acts as a Model-Context-Protocol (MCP) server, giving your AI coding assistant access to the full power of Chrome DevTools for reliable automation, in-depth debugging, and performance analysis. A CLI is also provided for use without MCP. - Get performance insights: Uses [Chrome DevTools](https://github.com/ChromeDevTools/devtools-frontend) to record traces and extract actionable performance insights. - Advanced browser debugging: Analyze network requests, take screenshots and check browser console messages (with source-mapped stack traces). - Reliable automation. Uses puppeteer to automate actions in Chrome and automatically wait for action results.

6 tools · click, lighthouse_audit

Metabase includes a built-in Model Context Protocol (MCP) server that lets AI clients connect directly to a Metabase instance. It uses the [Streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-03-26/basic/transportsstreamable-http) and builds on Metabase's Agent API to expose tools for searching, navigating, querying, visualizing, and creating/updating content - all scoped to the connecting user's permissions. The legacy /api/mcp path still works as an alias for existing clients, but /api/metabase-mcp is the canonical URL to advertise.

6 tools · construct_query, create_dashboard

Mastra supports the Model Context Protocol (MCP), an open standard for connecting AI agents to external tools and resources. It serves as a universal plugin system, enabling agents to call tools regardless of language or hosting environment. Mastra can also be used to author MCP servers, exposing agents, tools, and other structured resources via the MCP interface. These can then be accessed by any system or agent that supports the protocol. To use MCP, install the required dependency: Mastra currently supports two MCP classes:

4 tools · Connect agents to external MCP servers, Expose Mastra agents via MCP

Access Mastra's documentation via Model Context Protocol (MCP). Works with Cursor, Windsurf, Cline, Claude Code, VS Code, Codex, or any MCP-compatible tool. Follow the official installation instructions. Fetch documentation from mastra.ai by path. Supports guides and API references. Navigate migration guides for version upgrades. Supports directory browsing, section listing, and keyword search. Read docs from installed @mastra/ packages in node_modules. All tools require projectPath parameter. Entry point showing all available documentation tools and recommended workflows.

6 tools · Explore installed packages, Fetch docs by path

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a Playwright-compatible SDK that adds AI functionality on top of playwright, as well as a no-code workflow builder to help both technical and non-technical users automate manual workflows on any website, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed.

6 tools · Authenticate with stored credentials, Download files via prompts

MCP server for the Computer-Use Agent (CUA), allowing you to run CUA through Claude Desktop or other MCP clients.

Connect your AI assistant to GitHub repositories, issues, pull requests, and search.

4 tools · create_issue, get_pull_request

Kubeshark MCP (Model Context Protocol) server enables AI assistants like Claude Desktop, Cursor, and other MCP-compatible clients to query real-time Kubernetes network traffic. The MCP provides the tools — AI skills teach agents how to use them. Skills turn raw MCP capabilities into domain-specific workflows like root cause analysis, traffic filtering, and forensic investigation. See the skills README for installation and usage. - L7 API Traffic Analysis: Query HTTP, gRPC, Redis, Kafka, DNS transactions - L4 Network Flows: View TCP/UDP flows with traffic statistics - Cluster Management: Start/stop Kubeshark deployments (with safety controls) - PCAP Snapshots: Create and export network captures - Built-in Prompts: Pre-configured prompts for common analysis tasks

6 tools · create_snapshot, enable_dissection

This MCP is a wrapper around the Instant Platform SDK. Add this MCP to your editor to enable creating, managing, and updating your InstantDB applications. Instant hosts the latest version of the server at https://mcp.instantdb.com. For modern clients that support streamable HTTP use https://mcp.instantdb.com/mcp. For legacy clients that require SSE use https://mcp.instantdb.com/sse. For more editor-specific instructions, see the public docs. If you haven't already, make sure to get a personal access token from your Instant dashboard.

3 tools · Connect via remote or local server, Create and manage InstantDB apps

MCP server for accessing Amazon Bedrock Knowledge Bases - Find and explore all available knowledge bases - Search for knowledge bases by name or tag - List data sources associated with each knowledge base - Retrieve information using conversational queries - Get relevant passages from your knowledge bases - Access citation information for all results - Focus your queries on specific data sources - Include or exclude specific data sources - Prioritize results from specific data sources - Improve relevance of retrieval results - Use Amazon Bedrock reranking capabilities - Sort results by relevance to your query

4 tools · Filter results by data source, list_knowledge_bases

This AWS Labs Model Context Protocol (MCP) server for CloudTrail enables your AI agents to query AWS account activity for security investigations, compliance auditing, and operational troubleshooting. It provides comprehensive access to CloudTrail events and CloudTrail Lake analytics, allowing agents to track API calls, analyze user activity, and perform advanced security analysis. This server gives AI agents seamless access to CloudTrail data through standardized MCP interfaces, eliminating the need for custom API integrations and enabling powerful security insights and audit capabilities.

4 tools · get_query_status, lake_query

Analyze CDK projects to identify AWS services used and get pricing information from AWS pricing webpages and API.

Get prescriptive CDK advice, explain CDK Nag rules, check suppressions, generate Bedrock Agent schemas, and discover AWS Solutions Constructs patterns.

Generate images using Amazon Nova Canvas with text prompts and color guidance.

Core AWS MCP server providing prompt understanding and server management capabilities.

A Model Context Protocol (MCP) server that brings Firecrawl to MCP-compatible AI agents — search, scrape, and interact with the live web for clean, agent-ready context. > Big thanks to @vrknetha, @knacklabs for the initial implementation! - Search the web and get full page content - Search an index built for coding agents: GitHub issues, merged pull requests, READMEs, and docs - Scrape any URL into clean, structured data - Interact with pages — click, navigate, and operate - Deep research with autonomous agent - Automatic retries and rate limiting - Cloud and self-hosted support - SSE support

6 tools · firecrawl_agent, firecrawl_crawl

Secure file read/write operations with configurable directory access controls.

3 tools · list_directory, read_file

Open-source localization engineering tools. Connect to Lingo.dev localization engineering platform for consistent, quality translations. Lingo API • Lingo React MCP • Lingo CLI • Lingo GitHub Action • Lingo Compiler for React (Early alpha) These tools connect to localization engines – stateful translation APIs you create on the Lingo.dev localization engineering platform. Each engine persists glossaries, brand voice, and per-locale instructions across every request, reducing terminology errors 16.6–44.6%. Or bring your own LLM.

3 tools · Prevent hallucinated APIs, Set up i18n in React apps

The Apify Model Context Protocol (MCP) server at mcp.apify.com enables your AI agents to extract data from social media, search engines, maps, e-commerce sites, and any other website using thousands of ready-made scrapers, crawlers, and automation tools from Apify Store. It supports OAuth, allowing you to connect from clients like Claude.ai or Visual Studio Code using just the URL. > 🚀 Use the hosted Apify MCP Server! > > For the best experience, connect your AI assistant to our hosted server at https://mcp.apify.com. The hosted server supports the latest features - including output schema inference for structured Actor results - that are not available when running locally via stdio.

6 tools · Create and manage tasks, Manage storage

Jitsu collects event data from your websites, apps and servers, and delivers it to your data warehouse and to whatever other tools you use. It covers the same ground as Segment, but it's MIT-licensed and self-hostable, so the whole pipeline can run inside your own infrastructure — or on Jitsu Cloud, same software, hosted. Data lands in minutes, not hours: Segment loads warehouses once or twice a day (hourly at best), while Jitsu delivers per destination in batches as frequent as a minute, or row-by-row where that suits the destination. And where Segment bills by Monthly Tracked User, Jitsu Cloud bills by event volume, so the bill tracks data rather than audience size — while self-hosting has no usage billing at all.

4 tools · Configure destinations and streams, Debug pipelines with Live Events

> [!NOTE] > > We’ve introduced Notion MCP, a remote MCP server with the following improvements: > > - Easy installation via standard OAuth. No need to fiddle with JSON or API tokens anymore. > - Powerful tools tailored to AI agents, including editing pages in Markdown. These tools are designed with optimized token consumption in mind. > > Learn more and get started at Notion MCP documentation. > > We are prioritizing, and only providing active support for, Notion MCP (remote). As a result: > > - We may sunset this local MCP server repository in the future. > - Issues and pull requests here are not actively monitored. > - Please do not file issues relating to the remote MCP here; instead, contact Notion support.

6 tools · Edit a page’s content with Markdown, Move a page to a different parent location

This repository contains a list of Google's official Model Context Protocol (MCP) servers, guidance on how to deploy MCP servers to Google Cloud, and examples to get started. These remote MCP servers are managed by Google, and are available via endpoint. Below are a few key remote servrs. For a comprehensive list of all remote MCP servers managed by Google in General Availability (GA) and public preview vist the supported products pager AlloyDB for PostgreSQL BigQuery Bigtable Cloud Resource Manager Cloud SQL for MySQL Cloud SQL for PostgreSQL Cloud SQL for SQL Server Compute Engine (GCE) Developer Knowledge API (Google Developer Documentation) Firestore Google Maps (Grounding Lite) Google Security Operations (Chronicle) Kubernetes Engine (GKE) Spanner Cloud Run (GA) Cloud Storage

6 tools · Access Google developer documentation, Generate images and video

The Firebase Model Context Protocol (MCP) Server gives AI-powered development tools the ability to work with your Firebase projects and your app's codebase. The Firebase MCP server works with any tool that can act as an MCP client, including: Firebase Studio, Gemini CLI, Claude Code, Cline, Cursor, VS Code Copilot, Windsurf, and more! An editor configured to use the Firebase MCP server can use its AI capabilities to help you: - Create and manage Firebase projects - Initialize new projects, list existing ones, and manage Firebase apps - Manage Firebase Authentication users - Retrieve, update, and manage user accounts - Work with Cloud Firestore and Firebase SQL Connect - Query, read, write, and manage database documents - Retrieve Firebase SQL Connect schemas - Generate schemas and operations with AI assistance - Understand security rules - Validate and retrieve security rules for Firestore, Cloud Storage, and Realtime Database - Send messages with Firebase Cloud Messaging - Send push n

6 tools · apphosting_list_backends, auth_get_users

Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to large language models (LLMs). It allows AI applications to connect with various data sources and tools in a consistent manner, enhancing their capabilities and flexibility. MCP follows a client-server architecture: - MCP Hosts: Applications like AI assistants or IDEs that initiate connections. - MCP Clients: Connectors within the host application that maintain 1:1 connections with servers. - MCP Servers: Services that provide context and capabilities through the standardized MCP.

Laravel Boost accelerates AI-assisted development by providing the essential context and structure that AI needs to generate high-quality, Laravel-specific code. Documentation for Laravel Boost can be found on the Laravel website. Thank you for considering contributing to Boost! The contribution guide can be found in the Laravel documentation. In order to ensure that the Laravel community is welcoming to all, please review and abide by the Code of Conduct. Please review our security policy on how to report security vulnerabilities.

2 tools · Generate Laravel-specific code with proper conventions, Provide AI with essential Laravel context

Fetch web content and convert HTML pages into LLM-friendly markdown output.

1 tool · fetch

The Bright Data MCP server gives AI agents real-time access to public web data. It exposes 69 tools covering: - Web search — Google, Bing, and Yandex results as structured data - Page scraping — any URL as Markdown or HTML, with bot detection, CAPTCHA solving, and proxy rotation handled automatically on every request - Structured data extraction — clean JSON from Amazon, LinkedIn, Instagram, TikTok, YouTube, X, Reddit, Facebook, Crunchbase, Zillow, and other major platforms, without parsing HTML - Browser automation — navigate, click, type, screenshot, and read pages in a remote browser session - LLM response collection — send prompts to ChatGPT, Grok, and Perplexity and get their answers back as structured data - Package registry data — npm and PyPI package versions, READMEs, dependencies, and metadata

5 tools · discover, scrape_as_markdown

The official MCP server implementation for the Perplexity API Platform, providing AI assistants with real-time web search, reasoning, and research capabilities through the Agent API and the Search API. The remote MCP server is hosted by Perplexity and is the easiest way to get started: same tools, nothing to install or update. The Cursor and VS Code buttons at the top of this page connect to it with one click. If your MCP client does not support remote servers yet, skip to the local server setup below. Connect over Streamable HTTP with your Perplexity API key:

4 tools · perplexity_ask, perplexity_reason

Persist assistant memory as a lightweight knowledge graph across sessions.

2 tools · create_entities, search_nodes

The Tavily MCP server provides: - search, extract, map, crawl tools - Real-time web search capabilities through the tavily-search tool - Intelligent data extraction from web pages via the tavily-extract tool - Powerful web mapping tool that creates a structured map of website - Web crawler that systematically explores websites - Tutorial on combining Tavily MCP with Neo4j MCP server - Tutorial on integrating Tavily MCP with Cline in VS Code Connect directly to Tavily's remote MCP server instead of running it locally. This provides a seamless experience without requiring local installation or configuration.

4 tools · Crawl a website systematically, Extract structured content from URLs

This is a Model Context Protocol (MCP) server that provides access to stock market data from Financial Datasets. It allows Claude and other AI assistants to retrieve income statements, balance sheets, cash flow statements, stock prices, and market news directly through the MCP interface. This MCP server provides the following tools: - get_income_statements: Get income statements for a company. - get_balance_sheets: Get balance sheets for a company. - get_cash_flow_statements: Get cash flow statements for a company. - get_current_stock_price: Get the current / latest price of a company. - get_historical_stock_prices: Gets historical stock prices for a company. - get_company_news: Get news for a company. - get_available_crypto_tickers: Gets all available crypto tickers. - get_crypto_prices: Gets historical prices for a crypto currency. - get_historical_crypto_prices: Gets historical prices for a crypto currency. - get_current_crypto_price: Get the current / latest price of a crypto curre

6 tools · get_balance_sheets, get_cash_flow_statements

Leverage Notte Web AI agents & cloud browser sessions for scalable browser automation & scraping workflows

The Figma MCP server brings Figma directly into your workflow by providing important design information and context to AI agents generating code from Figma design files. > [!NOTE] > Rate limits apply to Figma MCP server tools that read data from Figma. Some tools, such as those that write to Figma files, are exempt from the rate limits. > <br><br> > Users on the Starter plan or with View or Collab seats on paid plans will be limited to up to 6 tool calls per month. > <br><br> > Users with a Dev or Full seat on the Professional, Organization, or Enterprise plans have per minute rate limits, which follow the same limits as the Tier 1 Figma REST API. As with Figma’s REST API, Figma reserves the right to change rate limits.

6 tools · Generate code from selected frames, Generate designs from web pages

AI-optimized PostgreSQL expertise for coding assistants pg-aiguide helps AI coding tools write dramatically better PostgreSQL code. It provides: - Semantic search across the official PostgreSQL manual (version-aware) - AI-optimized “skills” — curated, opinionated Postgres best practices used automatically by AI agents - Extension ecosystem docs, starting with TimescaleDB, with more coming soon - Agent Skills via npx skills — works with Claude Code, Cursor, Codex, Gemini CLI, and 40+ other agents - a public MCP server that can be used with any AI coding agent, or - a Claude Code plugin optimized for use with Claude's native skill support.

3 tools · search_docs, tiger

This repo is the one-stop shop for building AI-powered products and businesses on top of Stripe. It contains a collection of SDKs to help you integrate Stripe with LLMs and agent frameworks, including: @stripe/ai-sdk - for integrating Stripe's billing infrastructure with Vercel's ai and @ai-sdk libraries. @stripe/token-meter - for integrating Stripe's billing infrastructure with native SDKs from OpenAI, Anthropic, and Google Gemini, without any framework dependencies. Stripe hosts a remote MCP server at https://mcp.stripe.com. This allows secure MCP client access via OAuth. View the docs here.

6 tools · Add Stripe plugin to Codex, Build autonomous agents