developer tools를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 21589개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Enables Claude to utilize tools provided by Model Context Protocol (MCP) servers.
Orchestrates a swarm of specialized Claude 3.7 Sonnet instances to generate optimally coherent responses through ensemble intelligence.
Automatically generates project documentation and serves it via MCP to improve AI development tool accuracy.
Provides automated smart contract analysis, verification, and certification for Ethereum smart contracts.
Provides daily activity and graduate metrics across multiple Solana launchpads.
Provides access to Cloudeka's cldkctl CLI functionalities as Model Context Protocol (MCP) tools for AI clients like Claude Desktop and Cursor.
Automatically identifies, extracts, and optimizes logo icons from websites using advanced recognition and selection algorithms.
Integrates AI assistants with Twitch chat via a Model Context Protocol (MCP) server.
Extends language models with on-the-fly multimodal generation capabilities for images, music, and videos.
Transforms codebases into intelligent embeddings, enabling semantic code search for large language models and multi-agent systems.
Define complex spreadsheets declaratively using Python or YAML, then export them to ODS, XLSX, or PDF formats.
Provides instant access to EMC emission limits, frequency allocations, restricted bands, and compliance requirements for various standards.
Provides large language models and AI agents with safe, structured, read-only access to verification artifacts for deterministic triage, root-cause analysis, and verification insights.
Enables AI agents to investigate phone numbers and emails for linked identities, platform registrations, and data breaches.
Monitor and wait for various system conditions and command outcomes without blocking agent execution or resorting to inefficient polling.
Maps shell commands to standard MCP tools using single-file YAML specifications.
Deploys AI agents with realistic user personas to validate user journeys and identify UX friction at scale.
Automates macOS applications in the background, enabling LLM clients to click, type, scroll, and inspect accessibility trees without activating apps or moving the cursor.
Manages an attention-based memory layer for LLM coding agents, centralizing project guidance and lessons learned for efficient retrieval.
Enables AI coding agents to execute sudo commands securely using a native OS password dialog, preventing password exposure.
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