"MCP servers from GitHub user smriti-AA" matching MCP servers:

Enables AI agents to query LLM and multimodal model benchmarks, pricing, speed, and track model updates via structured diffs using the Artificial Analysis public API.

Seven remote MCP servers exposing 51 published Apify scrapers as agent tools: company diligence, social listening, recruiting, real estate, lead generation, e-commerce and academic research. Billed per result, and a call that returns nothing is never charged.

Enriches user data by generating and providing social media profile links (Instagram, Facebook, Twitter, LinkedIn) based on user information like name and birth date.

An educational MCP server that wraps the Materials Project API, exposing tools to search chemical systems, get material summaries, find semiconductors by band gap, and retrieve crystal structure facts.

Provides GitHub open-source intelligence via MCP tools for discovering trends, evaluating repository health, comparing projects, and analyzing users, issues, and releases. It includes a CLI and can be used with AI assistants like Claude or Cursor.

A high-performance server for analyzing GitHub user starred repositories, providing insights into development trends, technology adoption patterns, and timeline tracking.

Provides MCP wrappers for Allen AI's Asta research tools, enabling AI agents to manage local document collections and perform deep literature searches. It supports automated report generation, PDF text extraction, and research hypothesis synthesis.

A strategic advisory agent that applies Clayton Christensen's frameworks, such as Jobs-to-Be-Done and Disruption Theory, to analyze business decisions. It enables users to evaluate organizational capabilities, explore historical case studies, and receive theory-grounded strategic insights.

An MCP server that provides access to Monarch Initiative's biomedical data through the Biolink API, enabling agents to query biological entities, associations, and knowledge graphs using natural language.

Enables AI agents to search for speakers and talks by date using the Sessionize API.

Enables AI assistants to load and query local GEDCOM genealogy files, supporting search, browsing, and family tree traversal.

MCP server that synthesizes user feedback from multiple sources into actionable insights. Aggregates reviews, support tickets, and survey responses to identify patterns and priorities.

Aggregates tech and AI signals from HackerNews, arXiv, Lobste.rs, and GitHub into a structured briefing. No authentication required.

Delivers comprehensive company intelligence in a single tool call, aggregating profiles, tech stacks, key people, news, and corporate data from any domain or company name. Sources data from Wikipedia, GitHub, OpenCorporates, and web scraping to provide structured business insights using only free public APIs.

Enables querying WikiTree genealogy data including profiles, ancestors, descendants, relatives, biography, photos, and categories via natural language.

Enables querying EU-funded research projects and ERC grants from the CORDIS knowledge graph, including full project records and ERC scheme listings, with server-side filtering and attribution.

MCP server for HumanPen that lets AI agents work on real documents (.docx, .pptx, .pdf) — humanizing content to lower AI-detection scores, converting citations, condensing, and translating while preserving formatting, tables, images, and citations.

MCP server that provides AI agents with access to public social media data, including hot lists, searches, content details, user profiles, posts, and comments from platforms like Douyin, Xiaohongshu, Bilibili, and Weibo.

An MCP server for college placement cells to analyze student profiles from bulk Excel data, search students, and access evidence-backed skill intelligence from resumes, GitHub, LeetCode, and portfolios. It provides tools for skill gap analysis and profile completeness evaluation.

Enables AI agents to run research queries across multiple public sources (Hacker News, Reddit, GitHub, Brave Search) in parallel, returning normalized results.