"How to Create 2D Fighting Games in Godot Engine" matching MCP servers:

Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.

An MCP server that brings difficulty-adaptive, multi-path reasoning to Claude Code. It implements the Actor-Critic-Planner-Reflexion (ACPR) pipeline for deep research synthesis.

A water treatment process simulation engine that exposes WaterTAP capabilities through MCP and CLI adapters, enabling AI agents to build, solve, and optimize flowsheets using natural language.

Provides secure, agentic Excel analysis and calculation capabilities, enabling users to inspect workbook structure, perform statistical computations, write formulas, and generate outputs through whitelisted MCP tools with audit trails and backups.

Enables B2B lead generation through Apify's Prospect Engine actor, supporting company enrichment, job discovery, contact finding, and full ICP-gated outreach workflows.

Connects Claude to Sketch Engine for corpus linguistics and text analysis, enabling queries on collocations, concordances, word usage, and more via natural language.

A quantitative finance MCP server providing 24 tools for option pricing, portfolio optimization, risk measurement, fixed income analysis, and utility functions, enabling AI clients to perform professional financial calculations.

A statistical analysis MCP server offering 30 tools for descriptive statistics, hypothesis tests, regression, and time series, all returning Markdown reports with automatic interpretations to enable AI agents to perform comprehensive data analysis.

MCP server for interacting with Google Earth Engine, enabling geospatial analysis such as dataset visualization, statistics computation, and search via AI assistants.

Enables AI agents to simulate wastewater treatment processes using natural language, with dual MCP and CLI adapters for flexible integration.

Provides a change-intelligence layer for BIM models, enabling diff analysis of Speckle versions with persona-specific lenses (coordination, cost, field) and a groundedness contract that separates verified facts from inferred impacts.

Read-only MCP server for the July 2026 survey of AI in open-source design systems, enabling agents to query 19 systems' affordances, coercion techniques, and platform data via 9 tools, 2 resources, and 2 prompts.

Omni-channel x402-gated MCP Oracle providing structured data across 12 verticals monetized via Base USDC micropayments.

Enables satellite imagery analysis through Google Earth Engine, allowing users to search datasets, calculate vegetation indices like NDVI, filter collections by location and date, and export imagery to cloud storage. Supports major satellite datasets including Sentinel-2, Landsat, and MODIS for applications like agriculture monitoring and deforestation tracking.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Provides structured behavioral analysis grounded in Panksepp's affective neuroscience and pattern matching to understand human intent and behavior through primary emotional systems and transition dynamics.

Enables interaction with an explicit ARC-AGI-3 world model through typed operations for actor/rule editing, deterministic simulation, rendering, and observation comparison.

Enables AI clients to search a local literature library via vector semantic retrieval, with automatic conversion of Zotero items and arbitrary files into Markdown (including OCR for scanned PDFs). It supports natural language queries and provides answers with page-level citations.

Query iOS App Store revenue and download estimates for any app directly from your agent. Two tools: estimate_app returns monthly revenue and downloads with a confidence label (verified / calibrated / modeled), and search_apps resolves an app name to its App Store id.

Superhuman data-driven science. Allows agents to upload any tabular dataset, specify a target column, and get validated predictive patterns (with p-values, effect sizes, and context from literature) that surface feature interactions and subgroup effects you'd otherwise miss. Many discoveries already made, free for open data!