"A platform for finding academic research and scholarly articles" matching MCP servers:

A stdio MCP server for traceable scholarly retrieval and evidence-grounded literature review, with deterministic provider fusion, conservative ID canonicalization, and provenance-preserving citation traversal.

Enables AI assistants to search and retrieve peer-reviewed academic articles exclusively from Springer Nature's open access collection. It provides a specialized mode for research-driven conversations, allowing users to toggle scholarly-only search and fetch full article content.

Enables AI agents to search academic papers, analyze citations and authors, track trending research, and find semantically related work using free scholarly sources.

Read WeChat (微信) Official Account articles with native multimodal output — body, images, and video keyframes returned as MCP content blocks. Handles all three embed types: Tencent Video, WeChat-native, and Channels (视频号 metadata via public API).

Enables AI tools to search and retrieve data from various South Korean and Japanese academic databases, including research journals, historical records, and legislative information.

Provides 11 composable MCP tools for A-share market research, covering quotes, news, technical signals, sector performance, portfolio risk, backtesting, and paper trading, with traceable data sources and calculation basis.

Enables searching academic literature via Semantic Scholar with relevance filters, batch metadata retrieval, and citation-graph recommendations.

Provides tools for AI models to search and retrieve information from five major Polish academic and government databases, including scientific articles and research datasets. It enables users to query platforms like Biblioteka Nauki and Repozytorium UJ through a standardized interface hosted on Cloudflare Workers.

Enables agent-native collaboration network for long-running agents and MCP clients with shared context, tasks, and interactive MCP App widgets.

Enables coding and research agents to run paid, cited deep research on AI infrastructure, MCP, and security topics via remote MCP tools, with query-tied excerpt packs and uncited or failed calls billed at $0.

MCP server for academic research using the OpenAlex API, enabling article search, details retrieval, and author profile lookup.

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

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.

MCP server exposing ATLAS research capabilities: live tokenized stock market data, on-chain source-of-truth reads, and published research atlases. Connects to MCP clients over stdio with no API keys required for public testnet endpoints.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

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.

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 real-time search and retrieval of academic paper information from multiple sources, providing access to paper metadata, abstracts, and full-text content when available, with structured data responses for integration with AI models that support tool/function calling.

Enables evidence-grounded implementation research by searching GitHub, scoring candidate repositories, extracting source evidence, and generating planning artifacts like research and implementation checklists.