AgentToolDrop

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Mastra

Builds TypeScript agents and graph-based workflows with memory, RAG, evals and model routing

Create a project with npm

npm create mastra@latest

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

Why you'd want it

Mastra is a TypeScript framework for agents and workflows that plugs into React, Next.js and Node apps or runs as a standalone server. It connects to 40+ model providers through one interface, has a graph-based workflow engine with .then(), .branch() and .parallel(), and can suspend an agent or workflow for human input and resume from stored state. It also covers conversation history, RAG, observational memory, MCP server authoring, evals and observability.

Best for

  • TypeScript and Next.js teams
  • Agents with human approval steps
  • Apps that need memory and RAG in one stack

Use it when

You want agents, workflows, memory and evals in one TypeScript framework instead of assembling separate libraries.

Skip it if

You work in Python. Features in ee/ directories (for example auth) need a Mastra enterprise license for production use.

Same category or shared tags.

  1. 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
  2. Builds, evaluates and deploys Python agents and graph-based workflows, optimized for Gemini

    • 21.9k stars
    • 38.9 stars/day since creation
    • pushed
    • v2.12.0 on
    • Apache-2.0

    Install with pip

    pip install google-adk
    Use it when, skip it if, stats for Google Agent Development Kit (ADK)

    Why you'd want it

    ADK is a code-first framework where you define agents, tools and orchestration in Python, then compose them into multi-agent hierarchies or graph-based workflows with routing, fan-out/fan-in, loops, retries and human-in-the-loop. It ships a CLI with an interactive runner, a local web UI for testing and debugging, an adk eval command, and deploy commands for Docker and Cloud Run, with Vertex AI Agent Engine for scaling. It is optimized for Gemini but model-agnostic, and tools can come from custom functions, OpenAPI specs or MCP.

    Best for

    • Teams on Gemini and Google Cloud
    • Multi-agent hierarchies
    • Agents that need built-in evaluation

    Use it when

    You want agent definitions, a local testing UI, evaluation and deployment to Cloud Run in one toolkit.

    Skip it if

    You are on Python older than 3.11. If Python is not your stack, ADK has separate Java, Kotlin, Go and TypeScript versions in other repos.

    Stats

    Stars
    21,854
    Last push
    Release
    v2.12.0,
    License
    Apache-2.0
    Pricing
    Open source
    Stars per day, since repo creation
    38.9
    Tier
    Standard, not ranked
  3. Connects LLM agents to your data with connectors, indexes, query engines and event-driven workflows

    • 52.5k stars
    • 36.4 stars/day since creation
    • pushed
    • v0.14.25 on
    • MIT

    Install with pip

    pip install llama-index
    Use it when, skip it if, stats for LlamaIndex

    Why you'd want it

    The LlamaIndex framework is a Python toolkit for context augmentation: data connectors ingest APIs, PDFs, docs and SQL, indexes structure the data, and query and chat engines retrieve context for the model. Agents can call a RAG pipeline as one tool among many, and Workflows add event-driven, multi-step processes with branching, retries and human-in-the-loop review. You can start with the llama-index starter package or install llama-index-core plus only the integrations you need from over 300 packages.

    Best for

    • RAG over private documents
    • Agents that query your own data
    • Pairing with LlamaParse for hard documents

    Use it when

    Your agent's main job is answering questions or taking actions over your own documents and data sources.

    Skip it if

    You want a framework that is its maintainer's main focus: the README says the company's primary focus has shifted to LlamaParse, while the OSS framework stays available.

    Stats

    Stars
    52,501
    Last push
    Release
    v0.14.25,
    License
    MIT
    Pricing
    Open source
    Stars per day, since repo creation
    36.4
    Tier
    Standard, not ranked

For agents

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

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

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