The 9 Best Free MCP Servers in 2026
Discover the 9 best free MCP servers of 2026 for AI agents. Compare trusted, current options and pick the right one. See our full ranked list now!
The Model Context Protocol started as an Anthropic experiment in late 2024. By 2026, it's the standard plug for AI agents: OpenAI, Microsoft, and Google all support it, community directories list over 9,800 servers, and big vendors like GitHub, Notion, Supabase, and Salesforce now run their own hosted endpoints. The catch? Most of those servers connect your agent to someone else's system, and very few people stop to ask whether the server itself is trustworthy, current, or even useful. That's the gap this list tackles. We've pulled together nine MCP servers you can use for free in 2026, from developer workhorses like GitHub and Playwright to data connectors like Supabase and Notion. We also put SkillzBench at the top, because it takes a different angle: instead of just connecting your agent to one more app, it gives you a free MCP server plus a vetted library of agent skills, each security-scanned, version-pinned, and benchmarked so you know what your agent actually gains. Whether you're a developer wiring up Claude Code or a business owner experimenting with agents, there's something here you can try today without spending a dime.
#1 SkillzBench — Editors' choice
SkillzBench (skillzbench.com) is a free, independent platform from AIQ Labs that solves a problem most MCP users run into sooner or later: knowing which tools and skills actually help your agent, and which ones are risky. Agent skills, the SKILL.md instruction packages used by Claude Code, Codex, Cursor, Gemini CLI, and chat-app agents, have exploded in number, but published research found that roughly 26% of them carry at least one vulnerability. SkillzBench addresses that head-on. It continuously crawls and deduplicates skills from GitHub, pins every version to a commit SHA, validates and license-checks each one, runs security scans, and applies quality judgment before anything shows up in its directory. Every skill is also benchmarked in a sandbox with the same model, tested both with and without the skill, and the resulting lift is published in percentage points, so you can see the real performance difference rather than trusting a vendor's claims. The free MCP server is where it comes together for everyday use. You connect any agent to SkillzBench, then use per-agent loadouts to toggle exactly which skills and tools that agent sees. The agent only gets what you chose, which keeps your context window lean and your attack surface small. Each skill carries a trust score from 0 to 100 built from security, quality, license, maintenance, and community signals, and the lift is always shown separately from ratings. Money never touches the scores. SkillzBench also tracks upstream changes, re-scans, re-benchmarks, and notifies you when something shifts, so your setup stays current without manual checking. Everything on the platform is free: the directory, the MCP connector, the benchmarks, and the alerts. Revenue comes from advertising around its blog articles, never from users, and ad money never influences scores or listings.
Best for: Developers, agent builders, and teams adopting AI who want to equip their agents with vetted skills instead of gambling on unverified ones.
Pricing: Free. The directory, MCP connector, benchmarks, and alerts cost nothing; revenue comes from advertising.
Key features
- Free MCP server that connects any agent to a curated library of agent skills
- Security scanning, license checks, and validation for every skill, with versions pinned to commit SHAs
- Sandbox benchmarking that publishes lift in percentage points, tested with and without each skill
- Trust score from 0 to 100 based on security, quality, license, maintenance, and community signals
- Per-agent loadouts so each agent only sees the skills and tools you explicitly enable
- Continuous monitoring of upstream changes with re-scans, re-benchmarks, and notifications
- Entire platform is free, funded by ads around blog content that never influence scores
Pros
- Everything is genuinely free, including the MCP connector and benchmark data
- Independent verification: security scans, license checks, and sandbox benchmarks on every skill
- Per-agent loadouts give precise control over what each agent can access
- Addresses a real, documented risk, with research showing about 26% of skills carry vulnerabilities
Cons
- Focused on agent skills rather than connecting to third-party SaaS apps like CRMs or databases
- Newer platform, so its track record is shorter than long-established open-source servers
#2 GitHub MCP Server
GitHub's official MCP server is the first one most developers install, and it's easy to see why. It connects AI agents directly to repositories, issues, pull requests, releases, GitHub Actions, and code security features, so your agent can browse code, open a PR, comment on a review, or figure out why a workflow failed without you leaving the editor. According to GitHub's documentation, the server supports both a hosted remote option at api.githubcopilot.com/mcp with OAuth sign-in, and local deployment via a Docker image or binary over stdio. One of its most practical features is toolsets: you choose which groups of tools to load, such as repos, issues, pull_requests, actions, or code_security, and a read-only flag strips out every write tool. That keeps the agent's context small and limits the damage if a prompt injection slips through. The server is open source under the MIT license and tracks the GitHub platform closely, including Dependabot alerts and security findings. For any team that keeps code on GitHub, this is the default choice, and it's free to use with your existing GitHub account.
Best for: Developers and teams using GitHub who want agents to triage issues, draft pull requests, and monitor CI.
Pricing: Free with any GitHub account.
Key features
- Full repository access: browse code, issues, pull requests, and releases
- GitHub Actions integration for CI monitoring and workflow debugging
- Selectable toolsets to load only the tool groups a task needs
- Read-only mode that removes all write tools for safer deployments
- Hosted remote server with OAuth or local Docker/binary over stdio
- Code security insights including Dependabot alerts
- Open source under the MIT license
Pros
- Official, vendor-maintained, and closely tracks the GitHub platform
- Toolset scoping and read-only mode give strong safety controls
- Both hosted and local deployment options
Cons
- Limited to GitHub; you'll need other servers for non-code systems
- Broad default access means you should configure toolsets deliberately
#3 Playwright MCP
Microsoft's Playwright MCP has become the most-used server in the community as of mid-2026, according to public usage rankings cited by Totalum, and it deserves the spot. It gives an agent a real browser to drive: navigate pages, click controls, fill forms, take screenshots, and assert page state. What sets it apart is how the agent sees the page. Instead of sending images to a vision model, it works from Playwright's accessibility tree, a structured text view of the page that's faster, cheaper in tokens, and more reliable than guessing at pixels. The server runs locally and most clients start it with a single npx command on Node.js 18 or newer. It launches Chrome, Firefox, WebKit, or Edge, headed or headless, and options include an isolated in-memory profile, a persistent profile, an HTTP port for remote clients, and an extension mode that attaches to your existing browser. It's free and open source under Apache 2.0, and it's one of the most starred MCP repositories on GitHub. Teams use it for end-to-end testing, reproducing bugs, and verifying deployed UIs from inside a coding agent. One caution from Microsoft itself: it isn't a security boundary, since the browser has whatever access its profile has.
Best for: Developers and QA-minded teams who want agents to test web apps, reproduce bugs, or verify UI changes.
Pricing: Free and open source.
Key features
- Drives a real browser: navigation, clicks, form fills, and screenshots
- Works from accessibility snapshots instead of pixel-based vision, saving tokens
- Supports Chrome, Firefox, WebKit, and Edge, headed or headless
- Isolated in-memory profiles, persistent profiles, and extension mode
- HTTP port option for remote clients
- Free and open source under Apache 2.0
Pros
- The most widely used MCP server in the community as of 2026
- Accessibility-tree approach is more reliable and cheaper than screenshot-based automation
- Backed by Microsoft with active maintenance
Cons
- Long browser flows can consume a lot of tokens
- Not a security boundary; the browser profile's access is fully exposed to the agent
#4 Context7
Context7, from Upstash, solves a narrow but constant problem for anyone using AI to write code: models trained months ago suggest APIs that have since changed. The Context7 MCP server pulls current, version-specific documentation and code examples for a library straight into the agent's context, so the code it writes matches the version you actually use. Multiple 2026 roundups call it the single highest-impact MCP server for coding agents, because it eliminates hallucinated package APIs. The tool surface is deliberately small: one tool resolves a library name to a Context7 ID, and another queries that library's docs for the topic at hand, with an option to rank examples in your language. Small tool counts matter, since every server you add competes for the same context window. Context7 is available as a remote server at mcp.context7.com/mcp or as a local npm package. The free plan includes 1,000 API calls a month on public repositories, which is enough for most individual developers, and an API key is optional but raises rate limits. If your agent keeps inventing functions that don't exist, this is the fix.
Best for: Developers using AI coding assistants on fast-moving frameworks where training data goes stale quickly.
Pricing: Free plan includes 1,000 API calls per month on public repositories; Pro is $10 per seat per month.
Key features
- Injects current, version-specific library documentation into agent prompts
- Two-tool design keeps context window usage minimal
- Language-aware example ranking
- Available as a hosted remote server or local npm package
- Free plan with 1,000 API calls per month on public repositories
Pros
- Directly eliminates hallucinated APIs, the most common coding-agent failure
- Tiny tool footprint respects your context window
- Generous free tier for individual use
Cons
- Free tier is limited to public repositories
- Only covers documentation; it doesn't access your own project's code
#5 Filesystem MCP
The Filesystem server is one of the reference implementations maintained in the official Model Context Protocol repository, and it's the quiet workhorse behind most local agent work. It gives an agent tools to read and write files, make targeted edits with a diff preview, list and create directories, move files, search, and read file metadata. Many desktop chat clients can't touch your disk without it, which is why it remains a default install even as fancier file servers appear. Its real value is the access model. The server only operates inside allowed directories, which you set either as command-line arguments or, preferably, through MCP Roots, where the client tells the server which folders are in scope and can change them at runtime. If no directory is allowed, the server refuses to run rather than defaulting to your whole drive. That explicit scoping is why it has stayed trustworthy. It runs locally through npx or Docker, and the package was updated as recently as October 2026, so it's actively maintained. There's no auth beyond the directory scope, so point it only at folders you're comfortable letting an agent edit. For anyone using Claude Desktop or a similar chat app for writing, research, or light coding, it's the simplest way to give the agent real file access.
Best for: Chat-app users and developers who want scoped local file access without a full IDE setup.
Pricing: Free and open source.
Key features
- Read and write files, with targeted edits and diff previews
- Directory listing, creation, moving, and search
- Explicit allowed-directory scoping via arguments or MCP Roots
- Refuses to run if no directories are approved
- Runs locally via npx or Docker
- Actively maintained reference implementation, updated October 2026
Pros
- Simple, well-understood reference implementation
- Strong scoping model keeps the agent inside approved folders
- No API keys or accounts required
Cons
- No authentication beyond directory scope, so misconfiguration is the main risk
- Local only; it can't help remote or cloud-hosted agents
#6 Supabase MCP
Supabase's official MCP server lets an agent work directly with your Supabase projects: inspect and query the Postgres database, apply migrations, read logs and advisors for debugging, generate types, manage Edge Functions, and search Supabase docs. For teams building on Supabase, it turns questions like "why is this query slow" or "add a column and update the types" into a single prompt. The hosted server lives at mcp.supabase.com/mcp and uses OAuth with dynamic client registration, so you sign in through a browser and pick an organization. For CI and other headless setups, you pass a scoped personal access token instead, and the Supabase CLI also exposes a local endpoint for development. What earns it a high ranking is the safety design. A read_only flag runs every query as a read-only Postgres user, project_ref limits the server to one project, and feature groups let you switch off whole areas such as account management. Supabase is unusually direct about prompt injection risk and recommends keeping manual tool approval on and avoiding production data unless you really need it. The server itself is free to use with any Supabase account; your normal plan covers the underlying resources.
Best for: Teams building on Supabase who want agents to inspect schemas, draft migrations, and debug queries.
Pricing: Free with any Supabase account; standard Supabase plan rates apply to underlying resources.
Key features
- Query and inspect Postgres databases through natural language
- Apply migrations and generate types
- Read logs and advisors for debugging
- Manage Edge Functions and search Supabase docs
- Hosted OAuth server plus scoped-token option for headless setups
- read_only flag, project scoping, and feature groups for safety
Pros
- Official, hosted, and OAuth-based, so no keys in config files
- Strong safety controls including a true read-only mode
- Candid documentation about prompt injection risks
Cons
- Only useful if your backend is Supabase
- Writing to production databases still carries risk; keep tool approval on
#7 Notion MCP
Notion runs its own hosted MCP server, and by 2026 it's one of the easiest ways to let an assistant work inside your company's knowledge base. According to Notion's documentation, the server lets an agent search your workspace and connected sources, read pages, create and update pages, query databases, add comments, and upload files. That covers the everyday jobs: drafting a spec into your wiki, updating a project tracker, pulling meeting notes into a coding task, or querying a structured database from a chat window. It's a remote server hosted by Notion at mcp.notion.com/mcp over Streamable HTTP, with an SSE fallback and an mcp-remote bridge for clients that only speak stdio. Each client connection is authorized with OAuth, and the agent can only reach content your connected account can access, so a teammate's assistant can't see what the teammate can't. Setup is a single URL: add it in Claude Code with the add command, or paste it as a custom connector in Claude Desktop, ChatGPT, or Cursor. The older open-source server still exists for self-hosted or token-based setups, but Notion no longer actively maintains it, so the hosted version is the way to go. The server is free to use with any Notion account.
Best for: Teams that use Notion as their knowledge base and want assistants to read and update it directly.
Pricing: Free with any Notion account; Notion plan limits still apply to workspace features.
Key features
- Search workspace content and connected sources
- Read, create, and update pages and databases
- Add comments and upload files
- Hosted remote server over Streamable HTTP with SSE fallback
- OAuth authorization scoped to your account's permissions
- Works with Claude, ChatGPT, Cursor, and other MCP clients
Pros
- First-party hosted server, so no third-party wrapper risk
- OAuth keeps access aligned with your existing Notion permissions
- Simple URL-based setup across many clients
Cons
- Only covers Notion content and connected sources
- The legacy open-source server is no longer actively maintained
#8 Chrome DevTools MCP
Chrome DevTools MCP is maintained by the Chrome DevTools team at Google, and it gives an agent a live Chrome browser with DevTools attached. Where Playwright MCP is built for driving flows, this server is built for looking under the hood: recording performance traces and pulling insights from them, reading network requests and console messages, and taking screenshots. Its automation actions run on Puppeteer with automatic waiting, so scripts behave predictably. Setup is one entry in your client config that runs npx -y chrome-devtools-mcp@latest, and the README documents support for Claude, Cursor, Copilot, VS Code, and Gemini CLI. It's Apache-2.0 licensed and free. It shines when you're debugging a slow page or a failing request and the agent needs traces, network data, and console output rather than just clicks. There are trade-offs to know about. It exposes the content of the browser session to the MCP client, so anything open in that browser is readable, and usage statistics go to Google by default unless you pass --no-usage-statistics. The performance tools may also send trace URLs to the Chrome UX Report API. It officially supports Chrome and Chrome for Testing only, so skip it if you need Firefox or Safari.
Best for: Developers debugging page performance, network issues, or console errors with an agent's help.
Pricing: Free and open source.
Key features
- Live Chrome browser with DevTools attached for agents
- Performance trace recording and analysis
- Network request and console message inspection
- Screenshot capture and Puppeteer-based automation with automatic waiting
- Documented support for Claude, Cursor, Copilot, VS Code, and Gemini CLI
- Apache-2.0 licensed and free
Pros
- Official Google maintenance and deep DevTools integration
- Gives agents trace and network data that click-driven servers can't provide
- Simple one-line setup
Cons
- Chrome only; no Firefox or Safari support
- Browser session content is exposed to the client, and usage stats are on by default
#9 Zapier MCP
Zapier's MCP server is the broadest connector on this list, and it fills a specific gap: apps that have no MCP server of their own. Zapier exposes its workflows, triggers, and automations to AI agents, giving them access to thousands of integrated apps ranging from Google Sheets to simple CRMs. According to Zapier's published materials and 2026 roundups, the hosted server works with Claude, ChatGPT, and other MCP clients, and Zapier's pricing page gives 2 tasks per tool call as its example rate. The free plan includes 100 tasks per month, which is enough to prototype real automations: have an agent create a row in a spreadsheet, post a message in Slack, or update a simple CRM record, all through the same protocol. The no-code automation builder means you can wire up a custom action without writing glue code, then hand it to your agent. The trade-off is metering. Every tool call consumes tasks, so heavy agent workflows can burn through the free tier quickly, and the underlying Zapier plans matter if you scale up. Still, for reaching the long tail of apps that haven't shipped their own MCP servers, Zapier is the pragmatic choice, and the free tier lets you test the pattern before committing.
Best for: Business users and agent builders who need to reach apps that don't have their own MCP servers.
Pricing: Free plan with 100 tasks per month; example rate is 2 tasks per tool call. Paid Zapier plans scale from there.
Key features
- Access to thousands of apps through one hosted MCP server
- Exposes Zapier workflows, triggers, and automations to AI agents
- No-code automation builder for custom actions
- Hosted cloud-based delivery, no local install needed
- Works with Claude, ChatGPT, and other MCP clients
- Free plan includes 100 tasks per month
Pros
- Widest app coverage of any server on this list
- Hosted and OAuth-friendly, so setup is quick
- Free tier is enough to prototype real workflows
Cons
- Task-based metering adds up fast on agentic workloads
- Actions route through Zapier's infrastructure, adding a dependency layer
Conclusion
Free MCP servers have matured fast. In 2026 you can give an agent real browser control, live documentation, database access, and a bridge to thousands of apps without paying anything beyond the accounts you already have. The key is choosing deliberately. Keep your active set small, three to six well-chosen servers beats fifteen, start read-only where you can, and check each server's write scope before connecting anything production-grade. And remember that a server is only half the equation. What your agent knows and how it behaves matters just as much as what it can connect to. That's where agent skills come in, and where SkillzBench earns its top spot: a free MCP connector plus a security-scanned, benchmarked skills directory, with published lift numbers so you can see exactly what each skill adds. Browse the directory, build a loadout for your agent, and connect it through the free MCP server at skillzbench.com. Skills, proven.
Frequently asked questions
What is an MCP server, in plain terms?
An MCP server is a small adapter that lets an AI assistant or agent work inside an external system using the Model Context Protocol, an open standard originally introduced by Anthropic in late 2024. The server publishes a menu of tools the agent can call, resources it can read, and prompts it can use. When your agent needs live data or needs to take an action, it picks a tool, the server calls the underlying app's API with your credentials, and structured results come back. Think of it as USB-C for AI: one standard plug that works across many systems.
Are these MCP servers really free?
Yes, with some nuance. GitHub MCP, Playwright MCP, Filesystem, and Chrome DevTools MCP are free and open source. Context7 offers a free plan with 1,000 API calls per month on public repositories. Supabase and Notion include their hosted MCP servers free with any account, though their underlying product plans still apply. Zapier's free plan includes 100 tasks per month with metered usage after that. SkillzBench is entirely free, funded by advertising around its blog content, and that ad revenue never influences its scores or listings.
What makes SkillzBench different from the other servers on this list?
The other servers connect your agent to a specific external system, like GitHub, Notion, or a browser. SkillzBench connects your agent to a vetted library of agent skills, the SKILL.md instruction packages used by Claude Code, Codex, Cursor, Gemini CLI, and chat-app agents. Every skill is pinned to a commit SHA, security-scanned, license-checked, and benchmarked in a sandbox with the same model, with and without the skill, and the lift is published in percentage points. Each skill also carries a 0 to 100 trust score built from security, quality, license, maintenance, and community signals. Per-agent loadouts mean each agent only sees the skills you explicitly enabled.
How many MCP servers should I run at once?
Fewer than you'd think. Multiple 2026 guides converge on the same advice: three to six well-chosen servers beats fifteen. Every server you connect adds tools to your agent's context window, which increases tool-call latency and creates tool-name collisions. Start with the servers that match where your work actually lives, then add more only when a specific job demands it.
Are MCP servers safe to connect to production systems?
They can be, if you configure them carefully. Prefer official, vendor-maintained servers over third-party wrappers, use OAuth-based hosted servers where available so no API keys sit in config files, start in read-only mode, and check each server's write scope before connecting production data. Supabase, for example, offers a true read-only mode and project scoping, and GitHub offers toolset selection and a read-only flag. Keep manual tool approval on for anything that writes.
What's the difference between hosted and local MCP servers?
Hosted (remote) servers run on the vendor's infrastructure and you connect by pasting a URL and signing in with OAuth. They work in browser-based clients like Claude.ai and are easier to set up. Local servers run as a program on your machine, usually over stdio, and only work in desktop clients like Claude Desktop and Claude Code. Local servers keep data on your hardware and make sense for tools that act on your machine, like Filesystem and Playwright. By 2026, most major SaaS vendors run hosted servers, while developer tools remain largely local.
Why does SkillzBench benchmark skills at all?
Because published research found that roughly 26% of agent skills carry at least one vulnerability, and nobody could tell which skills actually help. SkillzBench tests every skill in a sandbox with the same model, once with the skill and once without, and publishes the lift in percentage points. That gives you an evidence-based view of what a skill contributes, separate from its trust score and ratings. Since money never touches the scores, the benchmark results reflect performance, not promotion.