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Uses Context7 MCP to fetch current library and framework documentation. Invoked for API references, setup questions, and code examples.

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG…

Audit context window consumption across agents, skills, MCP servers, and rules. Identifies token bloat, redundant components, and produces prioritized savings recommendations. Target: under 10 MCPs, under 80 tools active.

Use up-to-date library and framework docs via Context7 MCP instead of training data. Activates for setup questions, API references, and code examples.

Neural search via Exa MCP: web search, code examples, company intel, people lookup, and AI-powered deep research with semantic retrieval.

Unified AI media generation via fal.ai MCP: text-to-image, text/image-to-video with Seedance/Kling/Veo, text-to-speech with CSM-1B, and video-to-audio with ThinkSound.

Reference MCP server wrapping Brave Search API for web and local search with result ranking, filtering, and structured data extraction.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

This MCP server attempts to exercise all the features of the MCP protocol. It is not intended to be a useful server, but rather a test server for builders of MCP clients. It implements prompts, tools, resources, sampling, and more to showcase MCP capabilities.

Reference MCP server for web content fetching with HTML-to-Markdown conversion, robots.txt compliance, and configurable request parameters.

Reference MCP server for secure filesystem operations with configurable read/write permissions, directory scoping, and sandboxed file access.

A Model Context Protocol server for Git repository interaction and automation. This server provides tools to read, search, and manipulate Git repositories via Large Language Models.

Reference MCP server for GitHub operations covering repository search, issue/PR management, code analysis, and workflow automation.

Reference MCP server for Google Maps API covering geocoding, directions, place search, elevation data, and distance matrix calculations.

Reference MCP server implementing persistent memory using a knowledge graph. Stores entities, relations, and observations with natural language querying.

Reference MCP server for PostgreSQL database access with parameterized queries, schema inspection, and read-only mode support.

Reference MCP server for browser automation using Puppeteer. Covers page navigation, element interaction, screenshot capture, and form filling.

Reference MCP server for Sentry error tracking covering issue search, event analysis, and stacktrace inspection across projects.

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

MCP server construction with Node/TypeScript SDK: tool registration with Zod validation, resource and prompt handlers, stdio vs Streamable HTTP transport selection, and transport-independent server architecture.

Reference MCP server for Slack workspace integration covering channel management, messaging, user lookup, and thread operations.

Token consumption audit across agents and MCPs

Context7 MCP for live API docs

Node/TS MCP server with Zod validation

Surgical MCP usage — no context flooding, no silent mutations.