# Alternatives to OpenAI Agents SDK (Python) > Source: https://theagentsindex.com/openai-agents-sdk/alternatives (current datasheets, evidence-ranked) Candidates share the baseline category or are previously researched peers. Requirements, preserved strengths, explicit trade-offs and research coverage decide the order; paid tier does not. ## Shortlist ### 1. AgentsKit Composable MIT-licensed TypeScript packages for agent runtime, tools, memory, RAG and chat UI. **Research coverage:** 34/35 criteria **Where it improves on OpenAI Agents SDK (Python):** - [Writes code: yes — A bundled coder skill writes real multi-file TypeScript against scoped filesystem and allowlisted shell tools, so the agent you assemble authors code rather than snippets.](https://www.agentskit.io/docs/agents/skills/coder) - [Reviews code: yes — A codeReviewer persona ships with the skills package and reviews diffs for bugs, security and style in pull-request comment format; you host the review loop yourself.](https://www.agentskit.io/llms.txt) - [Claude: yes — A native Anthropic adapter covers the Claude family with streaming, tool calls, vision and long context, and the homepage demo configures Claude as the runtime adapter.](https://www.agentskit.io/llms.txt) **Trade-offs against OpenAI Agents SDK (Python):** - No researched regression against the baseline. [View AgentsKit](https://theagentsindex.com/agentskit) ### 2. Google Agent Development Kit (ADK) Open-source framework for building, evaluating and deploying AI agents in Python, TypeScript, Go, Java or Kotlin. **Research coverage:** 34/35 criteria **Where it improves on OpenAI Agents SDK (Python):** - [Claude: yes — Claude is supported in Python and Java, either through the registry wrapper on Google Cloud Agent Platform or directly against Anthropic with your own API key.](https://adk.dev/agents/models/anthropic/) - [Open models: yes — Open-weight models run through LiteLLM against local hosts such as Ollama, with separate documented paths for vLLM and on-device LiteRT-LM serving.](https://adk.dev/agents/models/ollama/) - [MCP server: yes — MCP works in both directions: agents consume external MCP servers as tools, and you can wrap ADK tools in an MCP server that any other MCP client can call.](https://adk.dev/mcp/) **Trade-offs against OpenAI Agents SDK (Python):** - No researched regression against the baseline. [View Google Agent Development Kit (ADK)](https://theagentsindex.com/google-adk) ### 3. Pydantic AI Open-source Python agent framework from the Pydantic team, with a typed agent loop and swappable models. **Research coverage:** 34/35 criteria **Where it improves on OpenAI Agents SDK (Python):** - [Claude: yes — Anthropic is a first-class built-in provider with its own model class and install extra, selectable by a provider-prefixed model string like anthropic:claude-sonnet-4-6.](https://pydantic.dev/docs/ai/models/overview/) - [Open models: yes — Open-weight models are reachable through OpenAI-compatible providers the docs enumerate, including local runtimes Ollama and vLLM as well as Hugging Face and Groq, so weights you host yourself are supported.](https://pydantic.dev/docs/ai/models/overview/) - [In a browser: yes — A browser chat interface ships in the package via Agent.to_web() or clai web, though the docs position it for local development and debugging rather than production use.](https://pydantic.dev/docs/ai/guides/web/) **Trade-offs against OpenAI Agents SDK (Python):** - No researched regression against the baseline. [View Pydantic AI](https://theagentsindex.com/pydantic-ai) ### 4. Agno Python SDK, open-source AgentOS runtime and hosted control plane for building and operating agents. **Research coverage:** 35/35 criteria **Where it improves on OpenAI Agents SDK (Python):** - [Writes code: yes — Ships a CodingTools toolkit whose documented job is editing files and running commands in a scoped project directory.](https://docs.agno.com/use-cases/coding-agents) - [Debugs and fixes: yes — Bug fixing is a documented pattern: reproduce, patch, rerun the failing tests.](https://docs.agno.com/use-cases/coding-agents) - [Reviews code: yes — Code review over a diff is one of the documented coding-agent patterns.](https://docs.agno.com/use-cases/coding-agents) **Trade-offs against OpenAI Agents SDK (Python):** - [Agent permissions: partial — Runs are unattended unless a tool is marked for approval; then the run pauses in your database until an admin resolves it.](https://docs.agno.com/agent-os/approvals/overview) - [Open source: partial — SDK and AgentOS are Apache 2.0; the control plane is the commercial part and is not published as source.](https://www.agno.com/compare/agno-vs-langgraph) [View Agno](https://theagentsindex.com/agno) ### 5. Letta Stateful agent harness, cloud and SDK for agents with persistent, git-versioned memory. **Research coverage:** 35/35 criteria **Where it improves on OpenAI Agents SDK (Python):** - [Writes code: yes — Agents edit and create files in your repository, including from GitHub issues and PRs.](https://docs.letta.com/platform/github-action/index.md) - [Debugs and fixes: yes — Vendor states coding agents debug failures and run test suites.](https://docs.letta.com/handbook/index.md) - [Reviews code: yes — Reviews diffs on demand or on every PR via the GitHub action's prompt input.](https://docs.letta.com/platform/github-action/index.md) **Trade-offs against OpenAI Agents SDK (Python):** - [MCP server: no — MCP runs inbound only: Letta sessions consume stdio, HTTP and SSE MCP servers; no Letta MCP server is published.](https://docs.letta.com/agent-sdk/mcp/index.md) - [Audit log: no — No administrative audit log is published; the Enterprise list stops at RBAC, SSO, quotas and dedicated support.](https://docs.letta.com/pricing/index.md) [View Letta](https://theagentsindex.com/letta) ### 6. Mastra Open-source TypeScript framework for building AI agents, with a hosted platform for running and observing them. **Research coverage:** 35/35 criteria **Where it improves on OpenAI Agents SDK (Python):** - [Done-for-you service: partial — You run the software, but Mastra sells professional services (Concierge, forward-deployed engineering) and enterprise support covering planning, prototyping and workshops.](https://mastra.ai/terms-of-service) - [Claude: yes — Anthropic is a named first-class provider in the model router; models are selected as provider/model-name strings.](https://mastra.ai/models) - [Open models: yes — Open-weight models run against any OpenAI-compatible endpoint on your own hardware; the vendor names gpt-oss, Qwen3 and DeepSeek.](https://mastra.ai/models) **Trade-offs against OpenAI Agents SDK (Python):** - No researched regression against the baseline. [View Mastra](https://theagentsindex.com/mastra) ## Method Unknown data is never treated as a benefit or a trade-off. Featured placement is labelled but cannot alter recommendation order.