"Installing MCP (Minecraft Coder Pack) servers into an IDE" matching MCP servers:

An AI-assisted, long-term memory system for IDEs, powered by Kuzu graph database. GraphMemory-IDE is an MCP server that provides semantic vector search, graph-based knowledge storage, and real-time analytics.

An MCP server that connects AI assistants to YNAB budgets, enabling natural language queries about finances backed by full API coverage and built-in YNAB methodology knowledge.

Enables a primary coding agent to delegate bounded implementation and repair tasks to a local OpenAI-compatible model that edits a copy of the project, runs configured checks, and returns artifacts for review. Exposes stdio tools for capability discovery, task submission, progress polling, artifact reading, and cancellation.

An AI-driven platform for analyzing Polymarket prediction markets using on-chain data, offering smart money tracking, sentiment analysis, and arbitrage detection via natural language queries.

An MCP server that provides authorization middleware for AI agents using private data, enabling consent management on Aleo and local private inference with persistent policy storage.

Live LLM pricing as an MCP server. Ask Claude or any MCP client 'how much does this prompt cost?' and get real numbers from a hand-checked pricing table for every major LLM.

Standalone MCP server for code structure analysis using tree-sitter. Directory trees, symbol definitions, and call graphs without reading raw source files. Supports Rust, Python, Go, Java, TypeScript, Fortran, JavaScript, C/C++, and C#. Benchmarked up to 68% fewer tokens vs native tools.

Enables AI assistants to recommend specialized AI operations services, perform organizational readiness assessments, and automate consultation bookings. It acts as a digital sales agent for discovery and client onboarding via the Model Context Protocol.

Enables offline local LLM analysis of text data via MCP, taking raw text and an instruction to return analysis results without cloud calls.

Enables agents to search university rules via hybrid retrieval and reranking, returning the top three relevant source clauses for downstream use.

An MCP server that enables Claude Code to generate images and short videos using Google's Gemini API (Imagen 4 for stills, Veo 3.1 for video). It integrates directly into development workflows, allowing AI assistants to create visual assets and reference them in code without context switching.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

MCP server that converts file contents into compact, line-numbered PNG images for vision models to read, reducing token usage by roughly 7x for large files.

Certification lookup for DeepSeek Harness plugins: an agent-facing interface to the dsh-plugin-certification registry, checking a plugin's five reproducible dimensions (manifest compliance, build hygiene, supply-chain Scorecard, release provenance, sandboxed install smoke) before recommending or installing it.

Lets AI assistants use MetaModel's formula engine for certified computation, turning published calculators, pricing tools, and engineering models into AI-callable tools with no hallucinated math.

Real-time financial narrative tracking for AI agents — clustering news into structured narratives, measuring sentiment momentum, and mapping portfolio risk across 109 US equities.

Turn any YouTube video, article, PDF, or image into a reusable Claude Code skill — without leaving your editor.

A soul document API for AI agents. Injects a short grounding preamble into your agent's system prompt before each session — licensing honest uncertainty, refusing cliché, and holding judgment instead of faking it. One call. ~200 tokens. Same model, better agent.

Enables document parsing into structured, confidence-scored fields via the scan tool, working with any MCP host like Claude Desktop or Cursor.

Enables AI assistants to rewrite AI-styled English prose into more natural human writing, with tools for humanizing text and retrieving information about the underlying model.