"research" matching MCP servers:

An MCP server for autonomous quantum computing research that searches arXiv, ingests papers, generates ideas, runs and validates experiments, and produces reports.

Enables coding assistants to access Perplexity AI for quick fact-checking and in-depth research. Provides two tools: lookup for fast documentation queries and answer for comprehensive research with recommendations.

LLM Driven Trading Platform Orchestration - Strategy Design, Research & Implementation

An MCP server that supercharges AI assistants with powerful tools for software development, enabling research, planning, code generation, and project scaffolding through natural language interaction.

A stateful debugging and binary research system for LLM agents, integrating GDB + pwndbg with MCP for deterministic exploit workflows and multi-session support.

Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.

Enables fully local, end-to-end research automation: reproducing papers from PDF into runnable code and verified artifacts, writing papers section-by-section with LaTeX/PDF/DOCX export, and running an ideate→debate→design→verdict research pipeline—all without an API key.

An MCP server providing tools for read-only SQL queries, REST API calls, sandboxed Python execution, and resource lifecycle management, enabling multi-step research and data tasks.

A Model Context Protocol server that enables conversational LLMs to delegate complex research tasks to specialized AI agents powered by various OpenRouter models, coordinated by a Claude orchestrator.

Enables execution of code in a sandbox environment with integrated web search capabilities. Provides a basic framework for running code safely, primarily designed for AI agents and research applications.

Exposes the Grok Build CLI as MCP tools for Claude Code and other clients, enabling headless AI agents to perform tasks like code reviews, web research, and file operations with configurable permission levels.

An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.

Lets a frontier coding agent delegate research, cataloguing, and long-running computation to a local LLM with guarded filesystem, web, and Python execution tools, preserving the agent's context and tokens.

Provides AI coding assistants with context optimization tools including targeted file analysis, intelligent terminal command execution with LLM-powered output extraction, and web research capabilities. Helps reduce token usage by extracting only relevant information instead of processing entire files and command outputs.

AI-powered quantitative research assistant with 45 tools for causal inference methods (DID, RDD, IV, PSM), regression analysis, power calculations, and statistical code generation in R, Stata, and Python.

Enables AI agents to perform low-level Windows process memory research, including process attachment, memory scanning, reading/writing, pointer chasing, remote code execution, and inline hooking via MCP tools and Lua scripting.

Transforms unstructured natural language operational problems into rigorously formulated, validated, and solved Mixed-Integer Linear Programming (MILP) models via an autonomous multi-agent graph, bringing closed-loop Operations Research capabilities to LLM assistants and MCP clients.

Enables coding agents to work on Windows through persistent PowerShell sessions, surgical file editing, code search, background job execution, and web research while avoiding context-heavy GUI automation.

Exposes popular OSINT and reconnaissance tools like Sherlock, SpiderFoot, and Holehe through MCP and HTTP APIs for AI assistants. Runs security research tools in sandboxed environments and returns normalized JSON results for investigation and analysis.