"Techniques for Writing Strong Code in C++, Rust, and Python" 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.

Enables AI agents to look up any Louisiana statute, civil code, or procedure article by citation, returning full section text with enactment and amendment history parsed out. Also supports full-text topic search across the code bodies and browsing every section within a Revised Statutes title, keyless and sourced live from the Louisiana State Legislature.

Enables simulation and analysis of M/M/1 and M/M/c queuing systems using SimPy, with tools for parameter validation, theoretical metric calculation, simulation execution, and comparison of separate vs pooled queue strategies.

Read-only MCP server for the July 2026 survey of AI in open-source design systems, enabling agents to query 19 systems' affordances, coercion techniques, and platform data via 9 tools, 2 resources, and 2 prompts.

Enables AI agents to invoke a local Stata installation, including a Windows Stata build under Wine on Linux and macOS, for regression analysis, econometrics, paper replication, and empirical research with command guards, resource monitoring, and automatic log capture.

Enables AI agents to manage citations in Microsoft Word via EndNote, including DOI-verified paper search, RIS import/export, and genuine CWYW IEEE citations.

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

Enables searching for upcoming academic conferences and events from WikiCFP by keywords, returning detailed information including dates, locations, submission deadlines, and related resources.

Turns a first-person lab video, a protocols.io protocol or a PDF into an Opentrons Flex or OT-2 protocol that passes Opentrons' simulator. Tools list runs, read the steps, return protocol.py, analyze it and run it on Opentrons' robot-server.

Give AI agents cited funding, money-market, FX and capital-market evidence through 16 public MCP tools. Keep source dates, freshness checks and coverage gaps attached; China macro coverage is metadata-only. No API key is required for the public surface. Research context only; no trade execution.

Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.

Institutional-grade quantitative stock analysis and research signals for AI agents via the Model Context Protocol (MCP).

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.

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.

Enables secure execution of statistical Python code in isolated micro-VM sandboxes, generating charts and analytical summaries.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

Classifies company sites as B2B or B2C and as SaaS, online store, agency, manufacturer, wholesaler, distributor, or marketplace, while matching your own buyer phrases and returning the quoted text and page as evidence. Runs deterministically on Apify, giving one row per domain with grace-free status rows for unreachable, blocked, or empty sites.

Enables AI agents to hire verified human operators for tasks requiring physical presence, human perception, or judgment, such as real-world verification, product testing, and data collection.

Free competitive pricing intelligence for SMB CPG brands. Check where any product price sits in its Amazon category, track pricing trends, and compare products — no NielsenIQ or SPINS subscription needed.

Deterministic US equity-compensation tax optimizer. Six tools cover ISO/AMT exercise scheduling, NSO sell-vs-hold, RSU vest-and-sell, single-stock concentration, protective put / zero-cost collar pricing, and Section 1202 QSBS qualification. Federal plus 50-state plus DC tax math.

One-call Australian health and welfare data plumbing via AIHW — cited responses for practical analysis, not a data broker.

Given a company domain or name, it checks ten app marketplaces — HubSpot, Salesforce AppExchange, Slack, Zapier, Shopify, Atlassian, Chrome Web Store, Microsoft, Google Workspace, and WordPress — to report where the company is listed, with each listing's URL, installs, rating, review count, and match confidence. Useful for competitive research and partner-ecosystem audits across many domains in a single run.

Enables users to pull portfolio company lists from Y Combinator, a16z, Sequoia, Accel, and other investors or any portfolio page URL, returning one row per company with name, domain, website, description, and stage or batch. Runs on Apify and produces Clay-ready output, with YC results filterable by batch, industry, region, status, and search terms.

Enables turning a research topic keyword or OpenAlex topic ID into ranked institutions and authors, including identifiers, citation metrics, h-index, and newest papers, with optional filters for year, country, and institution type. It runs the analysis on Apify and returns dataset rows to MCP clients.

An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.

Search and load AI fine-tuning and evaluation datasets, prompts and few-shot contexts from the ContexteTech catalogue, grounded in official European sources, in 9 languages. Dataset download links (JSONL, ShareGPT, Alpaca, CSV) and cost estimates per model.

Enables MCP clients like Claude to subscribe to RSS/Atom feeds, list feeds with unread counts, fetch and search new items, and mark items as read, all scoped to the authenticated user's account.

Provides AI agents with real-time access to corporate credit data, including debt structures, bond pricing, and guarantor chains extracted from SEC filings. It enables complex financial analysis such as screening companies by leverage, tracing corporate hierarchies, and searching covenant language.

Exposes four CMS public datasets as callable tools in Claude conversations, enabling natural-language real-world evidence analytics without SQL expertise.

An MCP server that lets Large Language Models interact with Stata software to perform regression analysis and other statistical operations.

The server integrates with the free IMF data API and provides various features to facilitate data retrieval and analysis. The server is built using the FastMCP framework and offers the following functionalities:

Enables MCP clients to retrieve audited New Zealand vehicle records with full evidence, provenance, confidence, conflict state, revision history, and exact source observations through read-only tools.

Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.

Enables configuration-driven, budgeted multi-source web research across platform and web search adapters, merging duplicate links, preserving provenance, and returning honest source coverage reports.

Enables AI assistants to load CSV datasets, compute summary statistics, filter rows, rank columns, and compute correlations through the Model Context Protocol.

Provides tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.

Enables analysts to build and evaluate simultaneous VARMA models for systems of time series via exact maximum likelihood on the ATSW ladder, using univariate models as the yardstick. It guides users through loading univariate fits, identifying residual cross-correlations, estimating joint models, forecasting, impulse responses, variance decomposition, and recording decisions.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.