"Resources and Tools for Financial Modeling" matching MCP servers:

An MCP server that exposes 218 Blender tools for full 3D modeling pipelines, with a LangGraph agent layer for planning, executing, observing, and reviewing modeling tasks with evidence-based verification.

An intelligent agent that responds to financial queries about TreePod Glamping directly within Claude Desktop using MCP protocol, providing tools for tariff calculation, occupancy checking, financial analysis, and business reporting.

Enables multi-agent financial research through MCP, combining live or offline market, news, fundamentals, document RAG, and risk tools with critic review, synthesis, and execution tracing.

A local MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.

A server that provides advanced mathematical and financial calculation capabilities for AI code assistants, enabling them to perform complex calculations like symbolic calculus, numerical methods, and financial analysis without implementing algorithms directly.

An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.

An MCP server that lets Claude control a Minecraft bot with 40+ actions including movement, combat, crafting, and inventory management. Built on Mineflayer, it supports Microsoft authentication, pathfinding, and auto-reconnect.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

An adaptation of the MCP Sequential Thinking Server designed to guide tool usage in problem-solving. This server helps break down complex problems into manageable steps and provides recommendations for which MCP tools would be most effective at each stage.

Pay-per-call tools for AI agents including trust checks, due diligence, market data, and human-verified approvals, settled in USDC on Base via the x402 protocol.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Transforms any prompt into a fully functional, production-ready product with zero human intervention by providing 150+ autonomous tools covering all aspects of software development.

A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.

An MCP server providing 22 pay-per-call utility tools for AI agents (scrape, validate, embed, store, moderate, notify, convert, prevent loops) without accounts or API keys, using USDC payments via the x402 protocol.

Enables building, optimizing, reviewing, and running AI agents and skills, plus managing authorized work items, in Erstan's QA environment via OAuth-authenticated MCP.

Enables AI-driven COMSOL batch jobs on the Harvard FASRC cluster, allowing users to run COMSOL models, manage jobs, and fetch results directly through natural language.