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

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.

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.

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.

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

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.

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

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

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.

Academic peer-review (HAKEM), research-gap finding, journal recommender (1,214 venues with predatory flags), duplicate publication checker, and article writer tools from Science AI Journal. Free local FTS5 tools + LLM-backed tools that bill the caller's account.

Enables coding agents to query AI model API prices, including historical point-in-time lookups with cited sources, using a bundled dated dataset and requiring no API keys.