"A server for conducting in-depth research on corporations and industries" matching MCP servers:

Read-only Hyperliquid and cross-exchange market research for AI agents, providing structured tools for live market data without requiring authentication.

Enables federated multi-source research by fanning out queries across web, community, and social sources, deduplicating and interleaving results, and storing a persistent corpus for cross-checking.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

A read-only FastMCP server for academic research that lets agents search papers, inspect metadata, follow citation graphs, generate BibTeX, and read full texts of open-access PDFs via semantic scholar, OpenAlex, arXiv, DBLP, and Crossref.

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

A deep-research MCP server exposing a single task-augmented tool that runs GPT-Researcher with Tavily search, Anthropic Claude, and OpenAI embeddings, streaming progress via MCP tasks and Upjack entity stream.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

MCP server for web research using anti-detect Camoufox browser. Enables search, page reading (including JS/SPA), batch fetching, clicking, typing, and live browsing sessions with caching and retries.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

An MCP server for deep research that performs search, scraping, synthesis, fact-checking, and persistent memory, enabling users to conduct comprehensive research tasks via Claude.

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 Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

Enables semantic search across personal PDF paper collections with page-level citations, allowing users to query their library from any MCP-capable client.

A unified MCP server for academic paper discovery, citation exploration, and research intelligence workflows over multiple scientific knowledge sources.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Browser-based research MCP server that drives a real Chromium browser via patched Playwright to access JavaScript-rendered content, dynamic tables, and login-walled dashboards. It provides tools for visiting URLs to extract DOM text and screenshots, and for performing structured data extraction using Anthropic Claude Sonnet.

Provides machine learning researchers with tools for creating publication-quality scientific visualizations, statistical plots, and 2D data representations. It streamlines the research workflow by enabling AI assistants to generate complex figures from CSV, JSON, or direct data inputs.