"All-in-One Local MCP (Model Context Protocol) Server" 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 integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.

A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.

MCP server that provides access to Chinese stock market data using akshare-one

Access to many public datasets right from your LLM application.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

Provides local, evidence-aware research memory with human review, revision history, and an inspector, allowing assistants to preserve source reports, inferences, assumptions, and evidence across sessions.

Provides read-only access to your local Zotero library via the Zotero Local API, enabling search, retrieval, and bibliography generation without API keys.

Enables users to search Korean local government project, plan, and budget documents through AI apps, compare cases across municipalities, and check planning, budget, and support conditions against original-source citations.

将akshare、yfinance、wbgapi、arxiv等免费公开接口封装为4个标准MCP工具，使支持MCP的智能体无需第三方账号和云额度即可直接查询金融市场、宏观经济和学术论文数据。

Enables AI assistants to search, browse, and cite a local Zotero 7 library with zero configuration and no API key, keeping all data on the user's machine.

A local CrossRef database MCP server enabling full-text search across 167M+ scholarly works, citation analysis, and impact factor retrieval without rate limits or internet dependency.

Enables AI agents to perform corpus analysis tasks such as discovery, search, and data access via the Model Context Protocol.

Provides comprehensive trading and market data functionality for Indian equity markets through Angel One's SmartAPI, enabling portfolio management, order placement, and real-time data queries.

Enables running the same prompt(s) across roughly 300 models from Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and others, then comparing per-model outputs, latency, token usage, error rates and billed cost side by side. Supports free cost estimates before launching, asynchronous run creation with status polling and cancellation, prepaid x402 credit top-ups, and an optional AI-written comparison summary of the results.

Enables searching and viewing 1.89 million entries of the Seungjeongwon Ilgi and 380,000 articles of the Annals of the Joseon Dynasty from a local PostgreSQL database via Claude Desktop.

Provides access to ancient text corpora via stdio, enabling corpus listing, status checks, searching, and text/metadata retrieval with provenance envelopes.

Enables AI assistants to read, search, and fully manage a Zotero library locally—organizing collections, editing items, uploading files, and managing notes, tags, and trash—through the local Zotero API without cloud sync.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.