AgentToolDrop

Deep Agents

Gives you a ready-made agent harness with planning, files, subagents and context management

Standard A well-known tool, listed for reference and not ranked. About tiers

Install with uv

uv add deepagents

Copied from the project's docs at github.com/langchain-ai/deepagents

Why you'd want it

Deep Agents is LangChain's opinionated agent harness on top of LangGraph, with subagents that get isolated context windows, a filesystem over local, sandboxed or remote backends, shell access, summarization of long threads and human approval of tool calls. It works with any model that supports tool calling, including local models through Ollama, vLLM or llama.cpp, and accepts your own tools or MCP servers. A JS/TS version lives in a separate repo, deepagentsjs.

Best for

  • Long-horizon, multi-step agents
  • Teams already on LangChain or LangGraph
  • Agents that need subagents and file access

Use it when

You want planning, subagents, files and context management working on day one, and still want to override any piece.

Skip it if

You need a custom control flow; LangGraph underneath gives you that directly. Its security model trusts the LLM, so you must enforce limits at the tool or sandbox level.

Related tools

Same category or shared tags.

  1. Claude Agent SDK

    Framework Standard

    Embeds Claude Code's agent loop, built-in tools and context management in Python or TypeScript apps

    • 8.3k stars
    • 16.9 stars/day since creation
    • pushed
    • v0.2.167 on
    • Python repo MIT

    Install with pip

    pip install claude-agent-sdk
    Use it when, skip it if, stats for Claude Agent SDK

    Why you'd want it

    The Agent SDK is a library that runs the Claude Code binary, so your agent gets the same tools (read, write and edit files, run commands, search the web), agent loop and context management that power Claude Code. You can add custom tools as in-process MCP servers, run hooks at points in the agent lifecycle, spawn subagents, control which tools run automatically through permissions, and resume or fork sessions. It is available for Python (claude-agent-sdk) and TypeScript (@anthropic-ai/claude-agent-sdk).

    Best for

    • Agents that edit files and run commands
    • Teams already using Claude Code
    • Embedding a coding agent in your own app

    Use it when

    You want Claude Code's tool set and permission model inside a process you operate, instead of writing the tool loop yourself.

    Skip it if

    You want to use non-Claude models. It needs an Anthropic API key or Claude through Amazon Bedrock, Google Cloud or Microsoft Foundry, and third-party products may not offer claude.ai login unless approved by Anthropic.

    Stats

    Stars
    8,283
    Last push
    Release
    v0.2.167,
    License
    Python repo MIT
    Pricing
    Paid
    Stars per day, since repo creation
    16.9
    Tier
    Standard, not ranked

    Full stat block for Claude Agent SDK

  2. LangChain

    Framework Standard

    Provides one interface and a large integration library for models, embeddings, vector stores and tools

    • 148k stars
    • 101 stars/day since creation
    • pushed
    • langchain-core==1.6.10 on
    • MIT

    Install with pip

    pip install -U langchain
    Use it when, skip it if, stats for LangChain

    Why you'd want it

    LangChain is a framework for building agents and LLM apps from interoperable components, with a large library of integrations for model providers, tools, vector stores and retrievers. Its standard model interface lets you swap models as you experiment without rebuilding the app. An equivalent JS/TS library, LangChain.js, is available, and it pairs with LangGraph for lower-level orchestration and LangSmith for evals and tracing.

    Best for

    • Apps that need many model or data integrations
    • Switching between model providers
    • Prototyping LLM apps in Python or JS

    Use it when

    You want ready-made integrations for models, vector stores and retrievers, and a single interface for switching providers.

    Skip it if

    You need fine-grained control over agent flow and state; the README points to LangGraph for advanced customization and agent orchestration.

    Stats

    Stars
    147,843
    Last push
    Release
    langchain-core==1.6.10,
    License
    MIT
    Pricing
    Open source
    Stars per day, since repo creation
    101
    Tier
    Standard, not ranked

    Full stat block for LangChain

  3. LangGraph

    Framework Standard

    Orchestrates long-running, stateful agents as graphs with durable execution and human-in-the-loop

    • 43.3k stars
    • 37.2 stars/day since creation
    • pushed
    • prebuilt==1.1.1 on
    • MIT

    Install with pip

    pip install -U langgraph
    Use it when, skip it if, stats for LangGraph

    Why you'd want it

    LangGraph is a low-level orchestration layer for agents and workflows that need to persist through failures and resume exactly where they left off. It provides short-term working memory and long-term memory across sessions, and lets a human inspect and modify agent state at any point during execution. It is built by LangChain Inc. but can be used without LangChain, and an equivalent JS/TS library, LangGraph.js, is available.

    Best for

    • Long-running stateful agents
    • Workflows with human review steps
    • Teams already using LangChain or LangSmith

    Use it when

    You want explicit control over an agent's control flow and state, with checkpoints it can resume from after a failure or a human review.

    Skip it if

    You want a quick agent with planning, subagents and file system use out of the box; the README points to Deep Agents, a higher-level package built on LangGraph, for that.

    Stats

    Stars
    43,287
    Last push
    Release
    prebuilt==1.1.1,
    License
    MIT
    Pricing
    Open source
    Stars per day, since repo creation
    37.2
    Tier
    Standard, not ranked

    Full stat block for LangGraph

For agents

The same entry, as files an agent can read without scraping this page. 

# read one entry
curl -s https://agenttooldrop.com/tools/deep-agents.md

# list the MCP servers in the catalog
curl -s https://agenttooldrop.com/tools.json \
  | jq -r '.tools[] | select(.category=="mcp-server") | .slug'