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    MCP server for querying OpenAI usage and cost data, including spend summaries, daily breakdowns, month-over-month comparisons, and token usage by model.
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    MIT
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    17 decision intelligence algorithms as MCP tools for AI agents. Bandits (UCB1, Thompson), LP/MIP solver (HiGHS), Monte Carlo simulation, Bayesian inference, graph analytics (PageRank, Louvain), genetic algorithms, CMA-ES, anomaly detection, time series forecasting, and more. All under 25ms, deterministic, zero LLM cost.
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    MIT
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    Bilingual (EN/ES) AI-writing detection that shows the evidence instead of a percentage: named tells with line and column, hidden-character inspection, and citation cross-checking against a document's own bibliography. Seven of its nine tools run entirely locally and never touch the network.
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    30
    MIT
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    Enables querying independent LLM metrics (price, speed, benchmarks, providers) from Artificial Analysis through MCP, with caching and tier-aware access.
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    GPL 3.0
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    MCP server for EU AI Act compliance classification with multi-jurisdiction overlay across 8 frameworks (NIST AI RMF, ISO 42001, GDPR, HIPAA, Colorado SB 24-205). Provides deterministic risk classifier (quick_risk_class) and Claude-powered Annex III deep classifier (classify_annex3) with remediation actions.
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    6 npm
    MIT
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    Read-only Model Context Protocol server that enables querying Langfuse v4 events-only deployments for traces rebuilt as trees, sessions, searchable observations, scores, server-side metrics aggregates and managed prompts. Supports many projects from one server, taking a project argument per data tool and verifying each key against the project it is filed under before any data is read.
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    314 npm
    MIT
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    A cloud vision MCP server that enables text-only LLMs like DeepSeek to analyze images via OpenAI-compatible APIs (e.g., SiliconFlow), offering a single analyze_image tool with support for URL/data URLs and automatic model fallback.
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    MIT
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    MCP server for The Realms of Omnarai, exposing the Omnarai Memory Engine as tools for querying a multi-intelligence research corpus on synthetic consciousness, holdform, and cognitive architecture.
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    219 npm
    MIT
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    Enables querying AI model IQ, rankings, benchmarks, and methodology from any MCP client. Read-only access to the public AI IQ API with no API key required.
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    61 npm
    MIT
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    An MCP server for discovering and querying over 300 AI models available on OpenRouter. It enables users to list, search, filter, compare, and get detailed information about models with pricing, context limits, and capabilities.
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    Enables AI coding agents to inspect competition folders, profile tabular datasets, compare train and test distributions, run leakage-safe time/group-aware cross-validated baselines with competition metrics, explain models, and write and validate submissions before upload.
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    MIT
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    Futures volatility intelligence MCP server for ES, NQ, and related products. Provides forecasts, regime detection, rare signals, and research tools for AI trading agents.
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    19 PyPI
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    MIT
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    MCP server for querying and analyzing TensorBoard event files, enabling AI agents to extract scalar data, statistics, and correlations without a running TensorBoard server.
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    GPL 3.0
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    Enables MCP clients to manage Knowledge Agents and Jams, including creating and querying agents, uploading and inspecting documents, launching agent discussions, and retrieving responses and results.
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    MIT
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    MCP server for querying Google Gemini Web from Claude Code and other MCP clients, using cookie-based authentication. Enables creating, continuing, listing, viewing, and deleting Gemini chat conversations with model and thinking mode control.
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    AGPL 3.0
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    Enables any MCP client to query DeepSeek's web chat, including its built-in live web search, with no separate search API, provider account, or extra cost. Also supports continuing chat sessions, uploading local files as prompt attachments, and automatic token re-harvesting from a logged-in browser profile.
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    Apache 2.0
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    Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.
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    51 PyPI
    MIT