Best Model Context Protocol (MCP) Servers in 2025

The Model Context Protocol (MCP) is an open standard that connects Large Language Models (LLMs) to real-world tools and data. While static chatbots like ChatGPT and Claude can summarize and respond, autonomous agents need more—they need structured, real-time context.

Think: product analytics for PMs, SEO data for marketers, or system logs for SREs.

That’s where MCP comes in. But to do anything useful, agents need an MCP server.

Compiled in June 2025, below are the top MCP servers on GitHub, ranked by stars.

🥇 github/github-mcp-server — 15.2k⭐

Let agents manage issues, pull requests, discussions, and more—backed by GitHub's identity and permissions model. A gold standard for building secure, API-aware agents.

🥈 microsoft/playwright-mcp — 11.6k⭐

Agents can trigger browser automation tasks using Playwright. Ideal for QA, scraping, and end-to-end testing workflows.

🥉 awslabs/mcp — 3.7k⭐

Exposes AWS documentation, billing data, and service metadata. Built by AWS Labs for internal and public-facing agents.

4. hashicorp/terraform-mcp-server — 575⭐

Secure, structured access to Terraform’s registry of providers and modules. Great for DevOps agents building infrastructure-aware workflows.

5. dbt-labs/dbt-mcp — 240⭐

Designed for analytics agents. Exposes dbt’s semantic layer, project graph, and CLI commands through a well-defined MCP interface.

6. getsentry/sentry-mcp — 173⭐

Gives agents access to Sentry error tracking and performance telemetry. A solid fit for observability-aware workflows.

7. mongodb-js/mongodb-mcp-server — 202⭐

Lets agents interact with MongoDB and Atlas instances securely. Built-in support for auth, structured queries, and access control.

8. StarRocks/mcp-server-starrocks — ~80⭐

Brings MCP to the StarRocks SQL engine. Tailored for data teams running BI and large-scale analytics workloads.

9. vantage-sh/vantage-mcp-server — ~57⭐

Focuses on cloud cost visibility. Lets agents retrieve usage patterns, billing trends, and cost-saving recommendations.

Key Takeaways

Most organizations aren’t asking, “Can we build an agent?”

They’re asking, “How do we build one securely?”

Before you start deploying these servers and give agents access to real tools and sensitive data, you should know these servers do expose sensitive data.

None of them come with guardrails. Agents can not only access your connected data, but autonomous agents can do just that… act autonomously.

That’s where Pomerium comes in.

Pomerium Secures Agentic Access

MCP is the protocol.

Pomerium enforces policy.

• Gate every request with identity

• Enforce rules based on role, time, or source

• Log and audit every action

• Block agents from going off-script

If your LLM can act, it needs policy.

• See how Pomerium secures AI agents

• Secure your MCP Servers with Pomerium for free