Popular
Read and write local files with configurable access controls.
filesystemfilesreadwrite
Trending now
Trending MCPs
The most active and widely-used MCPs among developers right now.
Popular
Real-time web search with privacy-focused results.
searchwebrealtimenews
Agent-Friendly
Structured step-by-step reasoning for complex problem solving.
reasoningthinkingagentsplanning
Persistent knowledge graph memory across AI conversations.
memorypersistenceknowledge-graphagents
Up-to-date library docs pulled directly into your AI context.
codingdocumentationlibrariesaccuracy
Browse by use case
Top MCPs by category
Each category is structured for direct answers. Find the right MCP for your workflow.
3 MCPs
Coding
Code generation, editing, and AI-assisted development tools.
1 MCPs
Filesystem
Read, write, and navigate local files and directories.
2 MCPs
Git
Git operations, repository management, and code review.
3 MCPs
Databases
Query, manage, and interact with databases via natural language.
2 MCPs
Web Research
Search the web, fetch pages, and extract online information.
2 MCPs
Automation
Automate workflows, processes, and repetitive developer tasks.
2 MCPs
AI Agents
Tools built specifically for agent memory, reasoning, and coordination.
Why it matters
Why builders use MCPs
Direct tool access
No copy-pasting. MCPs give models real tool access — read files, run queries, call APIs — without manual context passing.
Faster experimentation
Set up once, use anywhere. Add an MCP to your client and it is immediately available across all conversations.
Better agent workflows
Autonomous agents need real tools. MCPs are how you give an agent the ability to act, not just generate text.
Less manual context
Stop feeding the model file contents manually. MCPs handle retrieval so you can focus on the task.
Quick comparison
Most popular MCPs compared
A high-level comparison of the most widely used MCPs across key categories.
| # | MCP | Tags | Setup | Complexity | Labels | |
|---|---|---|---|---|---|---|
| 1 | Filesystem Read and write local files with configurable access controls. | filesystemfiles | 2 min | Low | PopularFast Setup | |
| 2 | GitHub Full GitHub API access: repos, PRs, issues, and code search. | gitgithub | 5 min | Low | PopularOfficial | |
| 3 | Context7 Up-to-date library docs pulled directly into your AI context. | codingdocumentation | 3 min | Low | TrendingBuilder Favorite | |
| 4 | Memory Persistent knowledge graph memory across AI conversations. | memorypersistence | 2 min | Low | Agent-FriendlyPopular | |
| 5 | Brave Search Real-time web search with privacy-focused results. | searchweb | 5 min | Low | PopularFast Setup | |
| 6 | PostgreSQL Query and inspect PostgreSQL databases via natural language. | databasesql | 3 min | Low | PopularFast Setup |
For detailed comparison within a category, see the category pages.
Recommended
Builder favorites
MCPs that developers install first and use most.
Popular
Read and write local files with configurable access controls.
filesystemfilesreadwrite
Popular
Query and inspect PostgreSQL databases via natural language.
databasesqlpostgresqueries
Popular
Real-time web search with privacy-focused results.
searchwebrealtimenews
Powerful
Full browser automation: navigate, click, screenshot, and scrape.
browserautomationscrapingpuppeteer
Agent-Friendly
Structured step-by-step reasoning for complex problem solving.
reasoningthinkingagentsplanning
FAQ
Frequently asked questions about MCPs
Direct answers to common questions about Model Context Protocol tools.
What is an MCP?
MCP (Model Context Protocol) is an open standard that lets AI models connect directly to tools, APIs, and data sources. Instead of copy-pasting context manually, an MCP-enabled model can read files, run queries, search the web, or call APIs on its own.
Why use MCPs?
MCPs eliminate the manual work of feeding context to AI models. They give models direct tool access — filesystem, databases, search, code execution — making AI assistants genuinely useful in developer workflows instead of just chat interfaces.
Which MCPs are best for developers?
For most developers, start with: Filesystem (local file access), GitHub (repo management), Context7 (accurate library docs), and either Postgres or SQLite (database access). These cover the most common use cases with minimal setup.
How do I choose an MCP?
Match the MCP to the task: need the AI to read/write files? Use Filesystem. Need current docs? Use Context7. Need GitHub operations? Use the GitHub MCP. Filter by complexity and setup time to find options that fit your workflow.
Are MCPs useful for AI agents?
Yes. MCPs are core infrastructure for autonomous agents. They give agents the tools to act — executing code, reading files, storing memory, searching the web — rather than just generating text. The Memory and Sequential Thinking MCPs are particularly agent-focused.
Do MCPs work with Claude, Cursor, and other tools?
Yes. MCPs work with any MCP-compatible client. Currently supported clients include Claude Desktop, Cursor, Zed, VS Code (with MCP extensions), and custom agent frameworks using the MCP SDK.
Ready to find your next MCP?
Browse by use case to find the right MCP for your workflow. Every page is structured for fast evaluation.