Compare

LangGraph vs Portkey

Portkey scores higher on the AgentReady, 63/100 against 34/100. They differ on 14 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

LangGraph. LangGraph is a low-level orchestration framework for advanced needs combining deterministic and agentic workflows, part of the LangChain ecosystem

Portkey. Portkey is a comprehensive platform designed to streamline and enhance AI integration for developers and organizations.

Where LangGraph is ahead

LangGraph passes llms-full.txt / full agent docs, and Portkey does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: copyable quickstart. Portkey misses it.

Where Portkey is ahead

Portkey passes clear product positioning and mcp discoverable, and LangGraph does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented, pricing understandable and limits / constraints documented. LangGraph misses those.

And on adopt, self-service signup, no mandatory sales call, agent-compatible signup flow, free trial or free allowance, cli available and mcp integration available. LangGraph misses those.

Finally, on operate, observable execution. LangGraph misses it.

What neither does

Both fail structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, programmatic credential creation, fast time to first request, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Portkey leads 93 to 73. LangGraph misses clear product positioning, mcp discoverable; Portkey misses llms-full.txt / full agent docs.

Understand. Portkey leads 38 to 15. LangGraph misses structured api reference, openapi / spec quality, authentication documented, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Portkey misses structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented.

Adopt is whether an agent can get a key and make its first successful call without a human in the loop. Portkey leads 80 to 25. LangGraph misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, cli available, mcp integration available; Portkey misses programmatic credential creation, fast time to first request, copyable quickstart.

Operate. Portkey leads 39 to 24. LangGraph misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified; Portkey misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

LangGraph does not publish a machine-readable starting price. Portkey starts at $0/mo and has a free tier.

Signal by signal

Which to pick

Portkey clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: LangGraph and Portkey. Alternatives to each: LangGraph, Portkey.

An agent can fetch this as data: POST /v1/compare {"slugs": ["langchain", "portkey"]}