"All About Docker" matching MCP servers:

Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.

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.

Stop hallucinating numbers. An MCP server that runs every math expression through four independent numeric engines in parallel and returns all four results side by side — so when they disagree, you know the answer is numerically unreliable.

MCP server for tinify.ai image optimization. AI-powered upscaling, resizing/cropping, compression, and SEO filename & alt text generation — all in one tool.

Generate and edit images with GPT Image 2.5 for $0.029 each, inside Claude, Cursor or any MCP client. A free you.bot API key comes with 50 credits (about 17 images) and needs no card.

Enables MCP clients like Claude Desktop to query DEXUN AdWhiz for ad account lists, AI recommendations, savings summaries, recent activity, and API quota, all read-only.

Hosted multi-model AI media + chat MCP server. Generates images, video, audio, face-swaps and talking-avatars, and chats across 300+ models (Claude, GPT, Gemini, DeepSeek…) - all from one balance and one API key.

Enables Claude to drive Google Flow end-to-end: batch video generation on Veo 3 / Omni 1.1, scene chaining, keyframe transitions, video-to-video edits, and automatic downloads, all through a local bridge with the OmniFlow Chrome extension.

Provides AI agents with structured knowledge about 67+ generative AI models, including model recommendations, prompt formatting, parameter guidance, and validation. It acts as a prompt engineering co-pilot that helps agents use their existing tools more effectively.

Enables agents to verify claims against cited evidence, screen content for prompt injection and relevance before reading it, and rank candidates by meaning, all with calibrated probability verdicts.

Enables Claude to explore, analyze, and answer questions about any public GitHub codebase by connecting to DeepWiki's AI-powered documentation.

Gives AI assistants read access to SDLC project artifacts stored in Supabase, enabling natural language queries about projects, artifacts, screens, and tech stacks, with optional IT cost estimation via Vertex AI Gemini.

Enables AI-assisted aquaculture manuscript writing through six specialized agents for literature review, drafting, results, abstract, copyediting, and integrity checks, all accessible from MCP-compatible chat clients.

Enables startup protection checks directly from your editor, analyzing clone risk, defensibility, and patentable features in about 2 minutes.

MCP bridge for Kimi Code native AgentSwarm with inference through ai&. Supports authenticated Streamable HTTP MCP and Docker deployment.

Model Context Protocol (MCP) stdio server built with the official MCP Python SDK (FastMCP). Exposes 3 MCP tools: package_capability, generate_dockerfile, generate_claude_desktop_config — package AIMarket capabilities as Docker images + MCP manifest + Claude Desktop config. Entrypoint: mcp_stdio_server.py; root Dockerfile + glama.json in repo.

160 tools that do that heavy lifting - storage, agent-to-agent collaboration, document conversions, identity verification -- almost all priced under a tenth of a cent or less per call.

NocturnusAI sits between your agent and the LLM. It extracts facts, reasons about what's relevant, and returns only what changed optimizing your token usage, saving you costs.

About MCP server for Google Agent Platform Docs — Google AI + Vertex AI. 3400+ pages searchable by AI agents.

Provides five safe tools (calc, search, model_drift, compare_runs, grade_answer) for arithmetic, keyword search, model drift monitoring, eval comparison, and answer grading against sources, all implemented directly from the MCP spec with zero dependencies.