Best MCP AI Skills & MCP Servers

MCP server that gives Claude real-time stock research — investment thesis, earnings analysis, insider signals, valuation, and bear/bull cases. Plus 20 utility tools.

MCP client for discovering and exercising resources, tools, prompts, and completions over stdio or OAuth-protected HTTP. Ships with a CLI, an interactive REPL, and a web dashboard served by `mcp-inspector serve`.

Node.js/TypeScript MCP server for Atlassian Confluence. Provides tools enabling AI systems (LLMs) to list/get spaces & pages (content formatted as Markdown) and search via CQL. Connects AI seamlessly to Confluence knowledge bases using the standard MCP in

Convert between formats and units — unit conversion, encoding, format transformation, naming conventions.

A Linear MCP server for interacting with Linear's API

List directory contents — entries, tree, glob, find.

Project-level understanding without reading all files — detect framework, language, conventions, and architecture.

Format data into various output formats — pretty JSON, YAML, markdown, ASCII tables.

AI agents drive your real Chrome via MCP — the kubectl for your logged-in browser.

Text search and replace across files — regex search, multi-file replace, grouped results.

MCP server exposing public instruction workflows as tools, backed by hidden AI agent skills for requirements, orchestration, quality, research, evaluation, governance, resilience, and physics-inspired analysis

Package version intelligence — latest version, diff, changelog, audit across npm/pypi/github/gitlab.

Knowledge infrastructure SDK for AI agents - universal references, multi-tier caching, storage abstraction, and sync

A command-line interface for MCP servers. curl for MCP.

Developer tools — loads shell, sandbox, batch for command execution and scripting.

Read files — full, head, tail, line range, encoding detection.

Complete filesystem operations — loads fileread, filewrite, filelist, fileops, filesearch.

File comparison — diff, patch, delta between files or versions.

Call graph analysis — callers, callees, call chains.

Your AI forgets everything between sessions. cachly fixes that permanently. Persistent memory + causal root-cause analysis for Claude Code, Cursor, Copilot & Windsurf. Learns from every bug fix, git commit, and CI run automatically. Arrives pre-briefed. P

Dependency graph analysis — imports, exports, circular deps, fan-in/out.

Rename refactoring — rename symbols across files, rename files with import updates, bulk rename with preview.

A Model Context Protocol server for the Linear API.

MCP server for Alexandria — 171 expert AI agents across 22 teams, accessible from Claude Desktop and Claude Code