Python AI Agent Skills

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Transcribe MCP Automate your transcriptions with AI. Transcribe MCP instantly connects your account to assistants like Claude, Windsurf, Cursor, and more so they can automate tasks on your behalf. The Local Server can add local files for transcription and return result to your Assistant in seconds. - ⚡ Fast, lightweight and LLM-friendly. No special ASR models needed, no setup and fighting python p

Start an OpenAI Codex CLI session for deep reasoning and code analysis

An MCP server for AI agents to explore DeFi yield opportunities, powered by DefiLlama. - Data Fetching Tool: The getyieldpools tool retrieves DeFi yield pool data from the DefiLlama, allowing filtering by chain (e.g., Ethereum, Solana) or project (e.g., Lido, Aave). - Analysis Prompt: The analyzeyields prompt generates tailored instructions for AI agents to analyze yield pool data, focusing on key

MifosX Self Service MCP is a Model Context Protocol (MCP) server built using FastMCP (Python). It exposes a set of AI-callable tools that allow MCP-compatible clients (such as Claude Desktop or DeepChat) to securely interact with the Apache Fineract / MifosX Self-Service APIs. This project enables AI-driven banking workflows such as authentication, account access, beneficiary management, and trans

A Model Context Protocol (MCP) server for summarizing homepage of the user or contents of subreddits and comments on posts. - Summarize user's reddit frontpage (homepage) with or without comment analyses. - Summarize a subreddit contents by inspecting posts sorted by hot, new, top, rising, random (if aviable) with or without comment analysis. - Summarize comments on a post. - Python 3.12 or higher

下面是为你的 bilibili-mcp 工具生成的 README.md 示例： 一个用于获取 B 站热榜的 MCP 工具，基于 FastMCP 和 B 站公开接口。你可以通过注册到 Cursor 或其他 MCP 客户端，实时调用热门视频数据。 确保使用 Python ≥ 3.12，并安装以下依赖项： 你的主代码文件可以是 bilibilimcp.py，项目结构如下： 使用 uv 运行工具： FastMCP 会自动暴露一个名为 getpopular 的工具： 获取 B 站热榜视频信息，返回最多 topk 个条目（最大 10 条）。 - 使用 httpx 实现异步请求 - 通过 FastMCP 注册为标准 MCP 工具 - 支持通过 stdio 与 MCP 客户端通信（例如 Cursor） - 仅用于学习与研究，B 站接口为公开接口，使用时请避免过于频繁访问。 - 默认 User-Agent

1. **Project Overview**:

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mcp-name: io.github.aikts/yandex-tracker-mcp A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with Yandex Tracker APIs. This server provides secure, authenticated access to Yandex Tracker issues, queues, comments, worklogs, and search functionality with optional Redis caching for improved performance. Documentation in Russian is available here / Документац

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An MCP server that provides safe access to your iMessage database through Model Context Protocol (MCP). This server is built with the FastMCP framework and the imessagedb library, enabling LLMs to query and analyze iMessage conversations with proper phone number validation and attachment handling. - macOS (required for iMessage database access) - Python 3.6+ Install all required dependencies: - fa

Overview • Quick Start • Supported Data Providers • FinData is an open-source Model Context Protocol(MCP) Server that provides professional financial data access capabilities for LLM. It supports various data providers such as Tushare, Wind, DataYes, etc. This enables AI applications to quickly retrieve financial data. Fully supports both Stdio and SSE transports, offering flexibility for differen

Role Definition

A Model Context Protocol (MCP) server implementation for Azure Data Lake Storage Gen2. This service provides a standardized interface for interacting with ADLS2 storage, enabling file operations through MCP tools. Requires Python 3.13 or higher. Install the package using uv: 1 - Edit Claude Desktop Configuration: Open claudedesktopconfig.json and add the following configuration. On MacOs, the file

mcp-name: io.github.wmarceau/rideshare-comparison Compare Uber and Lyft prices for any route using Claude Desktop. Add to your claudedesktopconfig.json: Compare Uber and Lyft prices for a specific route. Example prompt: "Compare Uber and Lyft prices from SFO airport to downtown San Francisco" Get a list of cities with rideshare pricing data. Example prompt: "Which cities are supported for rideshar

CSL-Core (Chimera Specification Language) is a deterministic safety layer for AI agents. Write rules in .csl files, verify them mathematically with Z3, enforce them at runtime — outside the model. The LLM never sees the rules. It simply cannot violate them. Originally built for Project Chimera, now open-source for any AI system. This doesn't work. LLMs can be prompt-injected, rules are probabilist

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