"Optimizing AI Model Thinking, Token Usage, and Context Size" matching MCP servers:

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.

Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.

This server assists with A/B testing by calculating required sample sizes and necessary test durations. It provides a suite of significance tests, including z-test, chi-square, and Fisher exact methods, while evaluating the risks of premature peeking.

An MCP server for navigating thought processes using branches, supporting thought cross-references and priority tracking to enhance insight generation and structured idea exploration.

Enables formal logical reasoning, mathematical problem-solving, and proof construction across 11 logic systems including propositional, predicate, modal, fuzzy, and probabilistic logic. Integrates external solvers (Z3, ProbLog, Clingo) for advanced reasoning, with support for proof storage, argument scoring, and cross-system translation.

Enables MCP clients to look up domains, URLs, IPs/ASNs, email addresses, phone numbers, crypto wallets, and business records; run autonomous investigations; collect crawl artifacts; and perform evidence-backed scam checks with traceable provenance.

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.

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.

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

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.

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.

An MCP server implementation that leverages Google's Gemini API to provide analytical problem-solving capabilities through sequential thinking steps without code generation.

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

Enables MCP clients such as Claude, Codex, Cursor, and OpenCode to search and retrieve news articles and clustered real-world events from roughly 150,000 sources worldwide, with tools for keyword/concept/location/date filtering, full-text lookup by URI or URL, entity name-to-URI resolution, token usage checks, and raw access to any newsapi.ai API endpoint. Results are returned as compact JSON to conserve context, and both local stdio and remote HTTP deployment are supported.

Forecast time series in CSV files: deterministic skforecast workflows and the script that ran.

An AI Concierge replaces static forms with adaptive AI conversations that understand real situations, structure key information automatically, and trigger the right next step. Rigid forms cause drop-off, weaken qualification, and strip away context. Perspective uses adaptive AI to capture structured data and trigger automation, so you understand what truly matters to your customers and can make d

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

Access to many public datasets right from your LLM application.

Hosted open-source AI apps callable by agents over MCP, enabling multi-model comparisons with real metered costs and skills like PDF translation, deep research, slide generation, and direct model queries.

MCP server for semantic research: search arXiv, fetch papers, and answer questions grounded in the actual paper text via RAG tools, resources, and prompts.

Enables discovery of official DHS country, survey, and indicator metadata; retrieval of public aggregate estimates; assessment of comparison risks; and export of auditable CSV, JSON, Excel, or executable notebook bundles.

Enables AI-native statistical analysis and reproducible research workflows through MCP, including natural language planning, protocol-based analysis, Python/R cross-validation, and publication-ready figure generation.

Enables AI assistants like Claude to run backtests, fetch market data, list strategies, and analyze trading algorithms via natural language.

Provides source-grounded Christian research material with exact passages, provenance, and stable citations via a REST API.

A hosted MCP server exposing US hospital chargemaster cost data to AI assistants.

Provides provenance-aware access to selected Sefaria Bible context, including Targumim, Mishnah, Jewish commentary, Josephus/Philo, and lexicon lookups, with on-demand caching of long-tail Sefaria texts.

Enables AI-assisted CSV data quality profiling through MCP tools, offering analysis reports and quality scores while preserving privacy by processing only aggregated data.

Provides access to the latest AI trends by querying Google News RSS and Hacker News API, enabling AI assistants to retrieve real-time trending topics.

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.

Enables AI clients to analyze any company domain and determine its AI maturity tier (commercialized, deployed, declared, or none) with supporting evidence, via a single tool backed by an Apify actor.