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Python 3.12+ Claude Agent SDK 15 LLM Providers 770 Tests

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What is Grip AI?

Grip is a production-ready AI agent platform built on the Claude Agent SDK with LiteLLM fallback for 15+ other providers. It’s designed for developers who need autonomous agents with real tool execution, persistent memory, and multi-channel deployment.
  • 115 Python modules (~21,200 lines of code)
  • 770 comprehensive tests ensuring reliability
  • 26 built-in tools across 16 modules
  • Self-hostable with Docker support
  • Multi-channel chat (Telegram, Discord, Slack)
  • REST API with bearer auth and rate limiting
Grip uses the Claude Agent SDK as its primary engine for Claude models, providing a full agentic loop with automatic tool execution and context management. For non-Claude models, it seamlessly falls back to LiteLLM with Grip’s internal agent loop.

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Key Features

Dual-Engine Architecture

Claude Agent SDK for Anthropic models with LiteLLM fallback for OpenAI, DeepSeek, Groq, Gemini, Ollama, and 10+ other providers

26 Built-in Tools

File operations, shell execution, web search (Brave + DuckDuckGo), deep research, task tracking, messaging, subagent spawning, finance, and more

Multi-Channel Chat

Deploy to Telegram, Discord, and Slack with bot commands, file handling, and voice message support

Task Tracking

Persistent task lists with workspace storage — active tasks auto-injected into system prompts so agents never lose context

Multi-Agent Workflows

DAG-based orchestration with dependency resolution and parallel execution using Kahn’s algorithm

Model Context Protocol

Native MCP server integration with stdio and HTTP/SSE transport — 14 preset servers included

Cron Scheduling

Natural language scheduling with channel delivery — perfect for reminders and periodic tasks

Dual-Layer Memory

MEMORY.md + HISTORY.md with TF-IDF retrieval, auto-consolidation, mid-run compaction, and semantic caching

Production-Ready API

FastAPI with bearer auth, rate limiting (30/min per-IP, 60/min per-token), audit logging, and security headers

Security First

Directory trust model, shell deny-list (50+ patterns), credential scrubbing, Shield runtime threat feed policy

Long-Running Tasks

Unlimited iterations by default with automatic mid-run compaction to prevent context overflow

Cost Optimization

Model tier routing for complexity-based model selection — simple queries go to fast/cheap models, complex tasks to powerful models

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Supported LLM Providers

Grip supports 15 LLM providers through its dual-engine architecture:
  • Anthropic (via Claude Agent SDK) — Claude 3.5 Sonnet, Claude 3 Opus, Claude 4 Sonnet
  • OpenRouter — Access to 200+ models from multiple providers
  • OpenAI — GPT-4o, GPT-4 Turbo, GPT-3.5
  • DeepSeek — DeepSeek Chat, DeepSeek Coder
  • Groq — Ultra-fast inference for Llama, Mixtral
  • Google Gemini — Gemini Pro, Gemini Flash
  • Qwen — Alibaba’s Qwen models
  • MiniMax — Chinese LLM provider
  • Moonshot (Kimi) — Long-context models
  • Ollama Cloud — Hosted Ollama models
  • Ollama Local — Self-hosted models via Ollama
  • vLLM — Local inference server
  • Llama.cpp — Quantized local models
  • LM Studio — Desktop LLM interface
  • Any OpenAI-compatible API — Custom endpoints supported
The Claude Agent SDK engine is recommended for Claude models as it provides the best agentic experience. For all other providers, use the litellm engine.

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Use Cases

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Development Automation

  • Code review and refactoring
  • Bug fixing with git blame integration
  • Documentation generation
  • Test writing and coverage analysis

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Research & Analysis

  • Deep web research with multi-step fact gathering
  • Data analysis and visualization
  • Financial market research (via yfinance)
  • Competitive intelligence gathering

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Operations & DevOps

  • Server monitoring and alerts
  • Deployment automation
  • Log analysis and debugging
  • Cron-based health checks

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Personal Assistant

  • Schedule management and reminders
  • Email composition and editing
  • Document generation
  • Multi-platform messaging

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Architecture Overview

Grip’s architecture is built around a central gateway that orchestrates all components: 
grip gateway
├── REST API (FastAPI)          27 endpoints
├── Channels                    Telegram, Discord, Slack
├── Message Bus                 asyncio.Queue decoupling
├── Engine (pluggable)          SDKRunner | LiteLLMRunner
├── Tool Registry               26 tools across 16 modules
├── MCP Manager                 stdio + HTTP/SSE servers
├── Memory                      Dual-layer with TF-IDF
├── Session Manager             Per-key JSON with LRU cache
├── Cron Service                croniter + channel delivery
├── Heartbeat Service           Periodic agent wake-up
└── Workflow Engine             DAG execution
For a detailed breakdown, see the Architecture page.

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Next Steps

Installation

Install Grip via PyPI or build from source

Quickstart

Get your first agent running in 5 minutes

Configuration

Configure engines, providers, and tools

API Reference

Explore the REST API endpoints

Build docs developers (and LLMs) love

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