"Resources for Coding in Python" matching MCP servers:

A Python MCP server that exposes local Ollama models as tools for AI assistants, enabling chat, generation, embeddings, and model management without cloud APIs.

Lets Claude Code delegate coding tasks to external models running on a local opencode serve, preserving main agent tokens for planning and review.

AI-powered cloud architecture - describe infrastructure in natural language, get Terraform, cost estimates, and compliance reports

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

A code-execution MCP server for Klaviyo and Shopify analytics, enabling safe JavaScript execution in a V8 sandbox with state persistence across calls.

Enables AI coding agents to offload yes/no, multiple-choice, and scoring questions to TypeSafe's Jev, returning compact confidence-scored answers to save tokens and improve speed.

Multi-model fusion analysis tool that sends queries to multiple AI models in parallel and returns structured analysis from a judge model.

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

Enables LLMs to see clipboard screenshots without saving files, using free Grok visual models, and integrates seamlessly with Command Code, Cursor, Claude, and other coding agents.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

Bazi (Four Pillars) charting MCP server with true solar time correction and multilingual output in Chinese, English, Japanese, and Korean.

Queries Claude Sonnet 4.6 and OpenAI GPT-5.5 in parallel via OpenRouter, returning structured multi-perspective responses for comparison and cross-checking.

Enables sending one identical brief to multiple LLMs in parallel and returning every answer verbatim, unmerged, unranked, and unsynthesized.

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

Enables users to perform deterministic time series forecasting through Claude by running reproducible Python statistical and foundation models, providing tools for loading data, cross-validation, forecasting, anomaly detection, and exporting re-runnable manifests without any LLM involvement.

Zero-dependency charts for Python and AI agents. SVG and PNG, 15 chart types, a one-line MCP server, and a Claude skill.

Enables coding or reasoning agents to request structured judgments from TypeSafe's Jev model at decision points, including choices, scores, claim verification, and code reviews, with probabilities and confidence returned as data.

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.

Code Intelligence Platform for AI Coding Assistants

Fresh, source-verified docs for building MCP servers and Claude agents, served to your AI coding agent over MCP. Each document is stamped with its source URL and last-verified date.