TL;DR
A searchable directory of 184+ MCP servers organized by category. Find the right server for databases, browsers, APIs, DevOps, and more.
The MCP ecosystem grew from a handful of reference implementations to a sprawling network of community-built integrations in under a year. That is both the good news and the problem. Finding the right server for a specific use case means sifting through GitHub repos, npm packages, and scattered README files.
We built the MCP Server Directory to fix that. It catalogs 184+ servers with working configurations, verified compatibility, and category-based browsing. Instead of guessing whether a server exists for Jira, Confluence, or your favorite database, you search once and get an answer.
This post walks through the top 10 servers by category - the ones that solve real problems for real workflows. If you want the full searchable list, head to mcp.developersdigest.tech.
Model Context Protocol is a standard interface between AI agents and external tools. You configure a server, and your agent gets access to whatever that server exposes - databases, APIs, file systems, browsers.
Every server in this directory follows the same pattern:
{
"server-name": {
"command": "npx",
"args": ["-y", "package-name"],
"env": {
"API_KEY": "your-key"
}
}
}
Paste the config into your Claude Code or Cursor settings and restart. The agent discovers the server's tools on startup.
The most battle-tested database server in the ecosystem. Read-only by default, which is exactly what you want when an AI agent is writing SQL against your data.
{
"postgres": {
"command": "npx",
"args": [
"-y",
"@anthropic-ai/mcp-server-postgres",
"postgresql://user:pass@localhost:5432/mydb"
]
}
}
Point it at a read replica for production use. The agent writes queries, runs them, and interprets results - no context-switching to a database client. The directory also lists servers for MySQL, SQLite, MongoDB, Redis, and DynamoDB for teams on different stacks.
Best for: Backend developers who answer data questions daily.
Full GitHub integration - repos, issues, PRs, branches, code review. This is the second server most developers install after filesystem, and for good reason. It collapses 20 minutes of PR review into a single prompt.
{
"github": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-github"],
"env": {
"GITHUB_TOKEN": "ghp_your_token_here"
}
}
}
Scope your token carefully. Read-only access for review workflows, full repo access only when you need the agent creating issues and PRs.
Best for: Anyone who lives in GitHub. Which is most of us.
Navigate pages, click elements, fill forms, take screenshots, read DOM content. This turns your agent into a QA engineer that can visually verify its own changes.
{
"playwright": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-playwright"]
}
}
The agent gets a headless Chromium instance. Pair it with screenshot-based debugging for fast iteration: deploy, open staging URL, verify, fix, repeat.
Best for: Full-stack developers doing visual QA and frontend testing.
Read channels, search messages, post updates. The agent can summarize day-long threads, extract action items, and post structured recaps - the kind of work that usually falls through the cracks.
{
"slack": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-slack"],
"env": {
"SLACK_BOT_TOKEN": "xoxb-your-bot-token",
"SLACK_TEAM_ID": "T01234567"
}
}
}
The directory lists similar servers for Discord, Teams, and Telegram if your team uses a different platform.
Best for: Team leads who spend too much time translating Slack threads into decisions.
Create issues, update status, query boards, add comments. When the agent finishes fixing a bug, it can create the issue, link the PR, and mark it done - all without you leaving the terminal.
{
"linear": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-linear"],
"env": {
"LINEAR_API_KEY": "lin_api_your_key_here"
}
}
}
The directory also covers Jira, Asana, Notion (as a project tracker), and Trello for teams on other platforms.
Best for: Engineers who want project management to happen as a side effect of coding.
Pull error reports, stack traces, and crash patterns directly into your coding session. The agent cross-references production errors with recent commits and suggests fixes based on real data.
{
"sentry": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-sentry"],
"env": {
"SENTRY_AUTH_TOKEN": "your-sentry-token",
"SENTRY_ORG": "your-org"
}
}
}
Datadog, PagerDuty, and Grafana servers are also in the directory for teams with different monitoring stacks.
Best for: On-call engineers and anyone debugging production issues.
Manage S3 buckets, query CloudWatch logs, inspect Lambda functions, and interact with other AWS services. Infrastructure questions that used to require the AWS console become single prompts.
{
"aws": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-aws"],
"env": {
"AWS_ACCESS_KEY_ID": "your-key",
"AWS_SECRET_ACCESS_KEY": "your-secret",
"AWS_REGION": "us-east-1"
}
}
}
The directory includes servers for GCP, Azure, Vercel, Cloudflare Workers, and Supabase. Pick the one that matches your deployment target.
Best for: DevOps engineers and anyone managing cloud resources alongside code.
Read pages, search workspaces, create content, update databases. Teams that store specs, PRDs, and runbooks in Notion can give the agent direct access to that context.
"Read the PRD for the auth redesign and implement the first phase" goes from a multi-step manual process to a single prompt when the agent can access Notion directly.
{
"notion": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-notion"],
"env": {
"NOTION_API_KEY": "ntn_your_integration_key"
}
}
}
Confluence, Google Docs, and Obsidian servers are also available for teams on other documentation platforms.
Best for: Teams with specs and docs in Notion who want agents that read before they code.
Web search from inside your agent session. Current documentation, recent release notes, Stack Overflow answers - all accessible without leaving the terminal.
{
"brave-search": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-brave-search"],
"env": {
"BRAVE_API_KEY": "your-brave-api-key"
}
}
}
The free tier is generous enough for development use. The directory also lists servers for Google Search, Exa, and Tavily if you prefer a different search backend.
Best for: Everyone. Agents with web access produce answers based on current information instead of stale training data.
Run arbitrary code in isolated cloud environments. Python, JavaScript, Bash - the agent experiments in a throwaway VM without touching your local machine.
{
"e2b": {
"command": "npx",
"args": ["-y", "@anthropic-ai/mcp-server-e2b"],
"env": {
"E2B_API_KEY": "e2b_your_key_here"
}
}
}
Sandboxes spin up in under a second. Critical for agents working on infrastructure scripts, deployment configs, or anything where a mistake on your local machine would be expensive.
Best for: Power users running agents on risky or experimental tasks.
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The full directory organizes all 184+ servers into searchable categories:
Each entry includes a working configuration snippet, required API keys, and notes on which AI clients support it.
Do not install 20 servers and hope for the best. Each server is a running process that consumes resources, and each one adds surface area for the agent to reason about. Three well-chosen servers outperform 15 loosely-related ones.
Start with your daily pain points. What tasks make you context-switch the most? If you constantly flip between your editor and GitHub, install the GitHub server. If you answer data questions all day, install Postgres. If Slack threads eat your mornings, install Slack.
Add one server at a time. Use it for a week before adding another. This gives you a clear sense of which servers actually change your workflow versus which ones sound good in theory.
Pair servers with a CLAUDE.md file. The CLAUDE.md generator creates project configuration that tells the agent how to use your specific servers. "Use Postgres to answer data questions. Use GitHub to create issues. Never modify production data." This gives the agent intent, not just access.
The MCP Server Directory is searchable, filterable, and updated as new servers ship. If you are building an MCP server and want it listed, submit it through the directory.
For configuring the servers you choose, the MCP Config Generator builds the JSON for Claude Code and Cursor without manual editing.
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