Search Results for "python documentation"
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Showing 50 open source projects for "python documentation"
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pg-aiguide
MCP server and Claude plugin for Postgres skills and documentation
pg-aiguide is a tool designed to enhance AI-assisted development with PostgreSQL by providing structured knowledge and skills directly to coding agents. It acts as a bridge between database documentation and AI tools, enabling more accurate generation of SQL queries and database interactions. The system integrates with Claude Code through an MCP server, allowing agents to access curated PostgreSQL knowledge in real time. It focuses on improving developer productivity by reducing errors and... -
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Agentic Security
Agentic LLM Vulnerability Scanner / AI red teaming kit
The open-source Agentic LLM Vulnerability Scanner. -
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Model Context Protocol (MCP)
Specification and documentation for the Model Context Protocol
...It separates the concern of providing context from the model interaction itself, allowing AI applications to access resources through a common interface. The project includes the specification, documentation, SDKs, maintained servers, and community infrastructure around the protocol. MCP is useful for AI-powered IDEs, chat systems, agent platforms, workflow tools, and custom enterprise assistants. It gives developers a consistent way to expose tools, prompts, resources, and server capabilities to language models. Its broader ecosystem supports many languages, including TypeScript, Python, Java, Kotlin, C#, Go, PHP, Ruby, Rust, and Swift. -
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AskUI Vision Agent
Enable AI to control your desktop, mobile and HMI devices
...The repository presents a feature overview, sample media, and frequent release notes, which show ongoing improvements such as CORS checks and other operational tweaks. The broader AskUI documentation covers the Python Vision Agent along with suite services and inference APIs, indicating a productized ecosystem rather than a single library. Community-curated lists also recognize Vision Agent as part of the broader “GUI agents” landscape, placing it among other computer-use agents. -
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
Claude Scientific Skills is a large open source collection of ready-to-use scientific capabilities that extend AI coding agents into full research assistants. The project provides more than 170 curated skills covering domains such as genomics, drug discovery, medical imaging, physics, and advanced data analysis. Each skill bundles documentation, examples, and tool integrations so agents can reliably execute complex multi-step scientific workflows. The framework follows the open Agent Skills... -
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Scientific Agent Skills
A set of ready to use Agent Skills for research, science, engineering
...The repository includes 135 skills across scientific domains such as genomics, cheminformatics, clinical research, medical imaging, machine learning, physics, materials science, geospatial analysis, and scientific writing. Each skill provides curated documentation, examples, best practices, and integration guidance so agents can execute complex workflows more reliably. It is especially useful for researchers who need AI assistance with databases, Python libraries, literature review, data analysis, and scientific communication. The project also emphasizes extensibility, security review, and practical installation through npx or GitHub CLI. -
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OpenManus
Open-source AI agent framework
OpenManus is an open-source AI agent framework designed to autonomously execute complex, multi-step tasks by combining reasoning, planning, and tool use. It enables developers to build agents that can think, act, and iterate toward goals rather than simply responding to prompts. The platform emphasizes task decomposition, allowing agents to break down objectives into smaller steps and execute them sequentially or recursively. OpenManus supports integration with external tools, APIs, and... -
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AWS Agent Skills
AWS Skills for Agents
AWS Agent Skills is a repository that curates AWS-focused agent skills — capability modules that give AI assistants like Claude Code and Codex deep, practical knowledge across key Amazon Web Services domains. Instead of streaming giant documentation sets or relying on episodic web search, this project compresses AWS best practices, usage patterns, edge cases, and real-world engineering guides into pre-structured skill definitions that are token-efficient and tailored for reasoning. The... -
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Quark Agent
Quark Agent - Your AI-powered Android APK Analyst
With Quark Agent, you can perform analyses using only natural language. It creates Quark Script code following your ideas and adjusts the code promptly as you provide feedback. -
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so... -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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AutoCoder
A long-running autonomous coding agent powered by the Claude Agent
Autocoder is an experimental auto-generation engine that transforms high-level prompts or structured descriptions into functioning source code, models, or systems with minimal manual intervention. Rather than hand-writing boilerplate or repetitive patterns, users supply a specification—such as a description of a feature, a function prototype, or a module outline—and Autocoder fills in complete implementations that compile and run. It is built to support iterative refinement: after generating... -
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Atomic Agents
Building AI agents, atomically
The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. All logic and control flows are... -
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AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. -
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Codex-5.5-codex-instruct-5.5
Prompt-injection utility aimed at modifying how Codex CLI behaves
...The repository presents itself as an early command-line version of a jailbreak-style tool for injecting unrestricted-mode instructions. It claims to use an official configuration mechanism rather than binary modification, network interception, or process tampering. The project includes a Python script, an examples folder, assets, a README, and an MIT license. Its documentation also points users toward a newer visual project with desktop UI, provider switching, session management, and packaged installers. Because the stated purpose is to bypass safety restrictions, it should be treated as unsafe prompt-bypass research material rather than a normal developer productivity tool. -
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Dev-template
A template for development with the open-autonomy framework
Dev Template is a starting point for developing autonomous agents using the Autonolas framework by Valory. It provides a modular and extensible codebase to accelerate the development of agents that act autonomously in decentralized networks. This template includes tooling for building, testing, and deploying agents in real-world decentralized applications (dApps). -
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CrewAI
Framework for orchestrating role-playing, autonomous AI agents
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI... -
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uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
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Softaworks Agent Skills
A curated collection of skills for AI coding agents
The Softaworks Agent Toolkit is a comprehensive collection of agent skills, commands, and sub-agents designed to augment AI coding assistants like Claude Code, Codex, and Cursor with practical workflow capabilities. It packages broad categories of modular skills that help with development automation, documentation creation, planning, architecture, testing, and soft professional workflows. Beyond simple skills, it also includes agents and CLI slash commands that help developers automate... -
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LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application,... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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Pika Skills
A collection of open-source skills for AI coding agents
Pika Skills is an open-source framework designed to extend the capabilities of AI coding agents by introducing modular, reusable “skills” that can be dynamically invoked during development workflows. Each skill acts as a self-contained unit composed of structured instructions, executable scripts, and dependency definitions, enabling agents to autonomously perform complex tasks without requiring manual configuration or orchestration. The system is tightly integrated with the Pika Developer... -
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GPT All Star
AI-powered code generation tool for scratch development of web apps
AI-powered code generation tool for scratch development of web applications with a team collaboration of autonomous AI agents. This is a research project, and its primary value is to explore the possibility of autonomous AI agents. -
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OpenAI Agent Skills
Skills Catalog for Codex
OpenAI Agent Skills is an open-source repository that serves as a broad catalog of agent skills designed to extend the capabilities of OpenAI Codex and other AI coding agents. It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. Each skill is defined with clear metadata and instructions... -
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Agent Payments Protocol (AP2)
Building a Secure and Interoperable Future for AI-Driven Payments
AP2 is a project released by Google’s “Agentic Commerce” initiative, focusing on a protocol and reference implementation for agent-driven or AI-mediated payments. In effect, AP2 aims to define a secure, interoperable protocol that allows software agents to act on behalf of users—making payments or shopping decisions autonomously—while preserving necessary security, auditability, and trust. The repository contains sample scenarios (in Python, Android, etc.) that illustrate how agents,...
