MCP servers that give coding agents real developer tooling: linters, package registries, test runners, language docs and local build commands. 13,951 servers in this category.
Provides coding agents with a suite of engineering tools including verification gates, repository maps, LSP, code graphs, and RAG.
Allows an AI client to inspect schemas and execute read-only SQL queries against a ClickHouse database.
Scaffolds production-ready FastMCP servers with built-in authentication, CI/CD pipelines, Docker support, and automated release workflows.
Provides an example application architecture to compare REST and MCP-based travel booking workflows and authentication methods.
Scans AI-generated GitHub repositories for security vulnerabilities like leaked keys, environment files, and SQL injection.
$claude mcp add --transport http vibescan https://vibescan.bigfloppy.net/mcp
Optimizes websites for AI agents by generating machine-readable assets like llms.txt, Markdown versions, API catalogs, and MCP server cards.
Converts existing source code into executable Functions, MCP tools, workflow Skills, and offline tests for AI coding agents.
Provides coding agents with a live knowledge graph of codebases to retrieve intent, co-change context, and architectural relationships.
Provides runnable modules for building AI agents, implementing RAG, managing memory, and deploying MLOps pipelines.
Generates Sphinx documentation for MCP tools, prompts, resources, and resource templates.
Enables coding agents to build, test, and evaluate reliable multi-step LLM workflows using typed files and local experiments.
Provides AI editors with code rationale by synthesizing git history, pull requests, and call-graph context.
An open-source, bilingual course providing hands-on labs for building reliable RAG systems, AI agents, and production-ready LLM applications.
Enables coding agents to generate, audit, and validate UI against declared design specifications and evidence-backed acceptance criteria.
Provides governed persistent memory for AI agents with contradiction detection, trust scoring, and belief lifecycle management.
Provides shared long-term memory for AI coding agents to record, recall, and consolidate project-aware context across multiple clients.
An agentic ecosystem for jw.org content featuring a massive MCP server with 129 tools, hybrid RAG, and local fine-tuning capabilities.
Enables an AI client to automate CST Studio Suite 2026 for electromagnetic modeling, solver configuration, simulation execution, and results verification.
Provides typed routing, local policy gates, and auditable receipts for AI agents to handle closed-question decisions.
Restores a complete Claude Code orchestration stack including 36 specialist agents, 162 skills, and MCP servers on a new Mac.