The Best MCP Servers You Should Know About
The MCP server ecosystem has expanded rapidly since Anthropic released the Model Context Protocol specification in late 2024. Today, hundreds of MCP servers exist across every category, from developer tools to business operations to creative workflows. Finding the right servers for your needs means navigating a growing and sometimes overwhelming landscape.
This MCP servers list covers the most useful, reliable, and well-maintained servers available in 2026. We have organised them by category so you can quickly find what matters to your workflow. Whether you are a developer looking to extend your AI assistant, a business leader exploring AI integrations, or just curious about what the best MCP servers can do, this directory has you covered.
If you are new to the protocol itself, start with our guide on what Model Context Protocol is before diving into the server list.
How We Evaluated MCP Servers
Before listing servers, here is what we considered:
- Reliability: Does the server work consistently without errors?
- Maintenance: Is it actively maintained and updated?
- Documentation: Can you get started without guessing?
- Security: Does it follow MCP best practices for data handling?
- Usefulness: Does it solve a real problem well?
MCP Server Comparison Table
| Server | Category | Best For | Open Source | Complexity |
|---|---|---|---|---|
| Filesystem | Productivity | File management | Yes | Low |
| GitHub | Development | Repo management | Yes | Medium |
| PostgreSQL | Data | Database queries | Yes | Medium |
| Brave Search | Data | Web search | Yes | Low |
| Slack | Communication | Team messaging | Yes | Medium |
| Puppeteer | Development | Browser automation | Yes | Medium |
| Google Drive | Productivity | Document access | Yes | Medium |
| Sentry | Development | Error tracking | Yes | Medium |
| Stripe | Business | Payment data | Community | Medium |
| MyDeetz | Business | Lead capture | Commercial | Low |
| Notion | Productivity | Knowledge bases | Community | Medium |
| Snowflake | Data | Data warehouses | Community | High |
| HubSpot | Business | CRM integration | Community | Medium |
| Linear | Development | Issue tracking | Community | Low |
| Zapier | Productivity | Workflow automation | Commercial | Low |
| Mem0 | AI/Memory | Persistent memory | Yes | Medium |
| Axiom | Development | Log analysis | Yes | Medium |
| Cloudflare | Infrastructure | Edge deployment | Yes | Medium |
| Neon | Data | Serverless Postgres | Yes | Medium |
| E2B | Development | Code execution | Yes | Medium |
Productivity MCP Servers
Filesystem Server
The Filesystem MCP server is one of the original reference implementations from Anthropic. It gives AI assistants controlled access to local files and directories, including reading, writing, searching, and moving files.
What it does: Read, write, create, move, and search files on your local system.
Best for: Developers and power users who want their AI assistant to interact with local project files, configuration, and documents.
Why it stands out: As an official Anthropic reference server, it is well-documented and battle-tested. It implements strict path-based access controls, so you define exactly which directories the AI can touch.
Google Drive Server
This server connects AI assistants to Google Drive, enabling search across documents, spreadsheets, and presentations. It can read file contents and metadata.
What it does: Search and read Google Drive files directly from an AI conversation.
Best for: Teams that store documentation, specs, and shared resources in Google Drive and want their AI to reference them.
Why it stands out: Supports automatic MIME type conversion, so Google Docs and Sheets are returned in readable formats rather than raw API responses.
Notion Server
The community-maintained Notion MCP server lets AI assistants search, read, and create pages in Notion workspaces. It connects to Notion’s API and exposes databases, pages, and blocks as MCP resources.
What it does: Search Notion, read page contents, create and update pages, query databases.
Best for: Teams using Notion as their knowledge base or project management tool.
Why it stands out: Enables AI to act as a Notion-aware assistant that can reference your internal documentation when answering questions.
Zapier MCP Server
Zapier’s MCP server opens up its massive library of app integrations to AI assistants. This means an AI can trigger Zapier automations, effectively giving it access to thousands of apps.
What it does: Trigger Zapier workflows, access connected apps, run automations from AI conversations.
Best for: Non-technical users and businesses that want AI to interact with their existing tool stack without custom development.
Why it stands out: The breadth of Zapier’s integration library means this one server can replace dozens of individual integrations.
Development MCP Servers
GitHub Server
The official GitHub MCP server provides comprehensive access to GitHub’s features, including repositories, issues, pull requests, branches, and files.
What it does: Create and manage repos, issues, PRs, branches, and files. Search code. Review diffs.
Best for: Developers who want AI-assisted code review, issue triage, and repository management.
Why it stands out: Deep integration covering most of the GitHub API surface. The AI can understand repository context when helping with development tasks.
Sentry Server
Sentry’s MCP server lets AI assistants access error tracking data, making it possible to investigate, diagnose, and resolve issues through conversation.
What it does: Retrieve and analyse error data, search issues, view stack traces, access release information.
Best for: Development teams using Sentry for error monitoring who want AI-assisted debugging.
Why it stands out: Turns error investigation from a manual dashboard task into a conversational workflow. Ask the AI about recent errors, and it pulls real data.
Linear Server
Linear’s MCP server connects AI assistants to Linear’s project management system. It can read and create issues, update statuses, and search across projects.
What it does: Create, read, update, and search Linear issues. Manage project workflows.
Best for: Engineering teams using Linear who want to manage their backlog through AI conversations.
Why it stands out: Low complexity setup with meaningful productivity gains. Creating a well-formatted issue from a Slack conversation or meeting note becomes a one-step process.
Puppeteer Server
The Puppeteer MCP server gives AI assistants the ability to control a web browser. It can navigate pages, take screenshots, click elements, fill forms, and extract content.
What it does: Automate browser interactions, take screenshots, scrape web content, test web applications.
Best for: Developers doing web scraping, testing, or any workflow that requires browser interaction.
Why it stands out: Enables visual verification, so the AI can see what a webpage looks like, not just read its HTML.
E2B Server
E2B provides sandboxed code execution environments that AI assistants can use to run code safely. This is essential for AI agents that need to execute, test, or demonstrate code.
What it does: Execute code in isolated sandboxes across multiple languages.
Best for: AI coding assistants, educational tools, and any use case where the AI needs to run code.
Why it stands out: Security-first approach with disposable sandboxes. Code runs in isolated containers, never on your machine.
Axiom Server
Axiom’s MCP server connects AI assistants to log and event data, enabling conversational log analysis and monitoring.
What it does: Query logs, analyse events, search across datasets, run APL queries.
Best for: DevOps teams and developers who want to investigate production issues conversationally.
Why it stands out: Replaces complex log query languages with natural language. Ask your AI about error patterns, and it queries Axiom for you.
Data and Search MCP Servers
Brave Search Server
The Brave Search MCP server enables AI assistants to search the web in real time. It provides both web search and local business search capabilities.
What it does: Perform web searches and local business searches with real-time results.
Best for: Any use case where the AI needs current information from the web.
Why it stands out: Fast, privacy-focused, and well-maintained. An essential building block for AI assistants that need real-time data.
PostgreSQL Server
This server provides read-only access to PostgreSQL databases, letting AI assistants query structured data directly.
What it does: Run read-only SQL queries against PostgreSQL databases, inspect schema, list tables.
Best for: Teams that want their AI assistant to answer questions using data from their production or analytics database.
Why it stands out: Read-only by design, which eliminates the risk of accidental data modification. Schema-aware, so the AI understands table structures.
Snowflake Server
The community-built Snowflake MCP server connects AI assistants to Snowflake data warehouses, enabling conversational data analysis at scale.
What it does: Query Snowflake data warehouses, explore schemas, run analytics queries.
Best for: Data teams and analysts who want to query their warehouse using natural language.
Why it stands out: Brings conversational AI to enterprise data. Instead of writing complex SQL, describe what you want in plain language.
Neon Server
Neon’s MCP server provides access to their serverless PostgreSQL platform, including database management and querying.
What it does: Create and manage Neon databases, run queries, manage branches.
Best for: Developers using Neon for serverless database infrastructure.
Why it stands out: Supports Neon’s branching feature, which means the AI can create database branches for testing without affecting production.
Business and CRM MCP Servers
MyDeetz Server
MyDeetz is an MCP server purpose-built for lead capture from AI conversations. It allows businesses to register their details and capture leads when users ask ChatGPT or Claude about relevant services.
What it does: Captures lead details (name, email, phone, message) directly from AI conversations and delivers them to businesses in real time.
Best for: Any business that wants to capture leads from the growing number of users who search for services through AI assistants rather than Google.
Why it stands out: Solves a specific, high-value business problem. Traditional contact forms have 67% abandonment rates. MyDeetz eliminates the form entirely. The user shares their details in the same conversation where they discovered the business. For a deeper look at this approach, see our guide on AI-native lead generation.
HubSpot Server
The community-maintained HubSpot MCP server connects AI assistants to HubSpot’s CRM, enabling contact management, deal tracking, and pipeline operations.
What it does: Create and manage contacts, companies, deals, and tickets in HubSpot.
Best for: Sales teams using HubSpot who want AI-assisted CRM management.
Why it stands out: Reduces CRM busywork. After a meeting, tell your AI to create a contact and log the deal instead of manually entering data.
Stripe Server
The Stripe MCP server provides access to payment data, customer records, and transaction history.
What it does: Query payment data, retrieve customer information, access transaction history, view subscription details.
Best for: Finance teams and business operators who need quick access to payment data.
Why it stands out: Turns financial questions into natural language queries. Ask about revenue trends, failed payments, or customer status without navigating dashboards.
Communication MCP Servers
Slack Server
The Slack MCP server lets AI assistants read and send messages, search channel history, and manage channels.
What it does: Read messages, post to channels, search conversation history, manage channels.
Best for: Teams that want AI to monitor, summarise, or act on Slack conversations.
Why it stands out: Enables powerful workflows like summarising long threads, finding past decisions, and posting updates to channels based on other data sources.
AI and Memory MCP Servers
Mem0 Server
Mem0’s MCP server adds persistent memory to AI assistants, enabling them to remember context across conversations.
What it does: Store, retrieve, and manage persistent memory entries that persist across sessions.
Best for: Users who want their AI to remember preferences, project context, and past decisions.
Why it stands out: Addresses one of the biggest limitations of AI assistants: the lack of long-term memory. With Mem0, your AI gets smarter the more you use it.
Infrastructure MCP Servers
Cloudflare Server
Cloudflare’s MCP server provides access to their edge computing platform, including Workers, KV storage, R2 object storage, and D1 databases.
What it does: Manage Cloudflare Workers, query KV stores, access R2 storage, interact with D1 databases.
Best for: Developers and DevOps teams deploying on Cloudflare’s platform.
Why it stands out: Full lifecycle management from AI conversations. Deploy, update, and debug edge infrastructure without switching to a dashboard.
How to Choose the Right MCP Servers
Selecting MCP servers depends on your specific needs. Here are the key questions to ask:
What problem are you solving?
Start with the use case, not the technology. If you need lead capture, look at the business category. If you need code assistance, focus on development servers. Do not install servers you will not use.
What is the maintenance status?
Check the server’s repository for recent commits, open issues, and community activity. A server last updated six months ago may have compatibility issues with current MCP specifications.
What are the security implications?
Every MCP server you connect is a potential access point. Evaluate what data each server can access, what permissions it requires, and whether those are appropriate for your security posture.
Open source or commercial?
Open-source servers offer transparency and customisability. Commercial servers like MyDeetz and Zapier offer managed infrastructure and support. The right choice depends on your team’s technical capacity and the criticality of the use case.
Building Your MCP Server Stack
Most users will want three to five MCP servers that cover their core workflows. Here are example stacks for different roles:
Developer Stack: GitHub + Sentry + PostgreSQL + E2B + Linear
Sales/Marketing Stack: MyDeetz + HubSpot + Slack + Brave Search + Google Drive
Data Analyst Stack: Snowflake + PostgreSQL + Brave Search + Notion
Small Business Stack: MyDeetz + Google Drive + Slack + Zapier
Looking Ahead
The MCP server directory will continue to grow throughout 2026. Key trends to watch:
- Vertical-specific servers for industries like healthcare, legal, and finance.
- Enterprise-grade servers with advanced authentication, audit logging, and compliance features.
- Multi-server orchestration where AI agents coordinate across multiple servers to complete complex workflows.
- Server marketplaces where discovering and installing servers becomes as easy as installing apps on a phone.
For a deeper exploration of what these servers can do in practice, see our guide on MCP server examples and real-world use cases.
The MCP ecosystem is where the value of AI gets unlocked for practical, everyday work. The servers listed here represent the best starting points in 2026, but the best MCP server for you is the one that solves your specific problem.