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Observability and Evaluation

LangSmith

Agent and LLM observability platform from LangChain for tracing, monitoring, and evaluating applications in production.

freemiumChecked 2026-10-07Source verified

Quick decision

Best for
Teams building with LangChain or LangGraph, or any framework, that want tracing connected to datasets, evals, and prompt workflows in one managed platform.
Not ideal for
Teams that require open source self-hosting on lower tiers, or that want flat usage pricing without per-seat charges.
Pricing model
Freemium model with a free Developer tier, a Plus tier priced per seat per month with included base traces and pay-as-you-go usage beyond that, and custom Enterprise pricing. Usage is metered in LangChain storage and compute units tied to trace volume and retention, as described on the LangChain pricing page.
Deployment
cloud. bring-your-own-cloud. self-hosted.
Authentication
API key via LANGSMITH_API_KEY environment variable, with optional workspace ID for org-scoped keys
Review state
Source verified. Facts checked 2026-10-07. Not locally tested by AgentsUse.

What it does

LangSmith is presented by LangChain as a framework-agnostic observability and evaluation platform for LLM applications and AI agents. The product page describes tracing for preferred frameworks or any agent stack using Python, TypeScript, Go, or Java SDKs, with native tracing for popular agent frameworks and OpenTelemetry.

Product areas on the page include step-by-step agent tracing to pinpoint latency, cost, and quality issues, monitoring with cost tracking and online LLM-as-judge and code evals, tool and agent trajectory monitoring, and alerts via webhooks and PagerDuty. Insights features automatically cluster traces to detect usage patterns and failure modes, supported by SmithDB, a purpose-built database for nested agent traces.

Deployment and data notes on the page cover managed cloud hosted at smith.langchain.com with data stored in GCP us-central-1, plus bring-your-own-cloud and self-hosted options on Enterprise where data can run in a customer Kubernetes cluster on AWS, GCP, or Azure. The SDK uses an async callback handler so tracing does not block application performance.

Verified capabilities

Observability

  • Agent tracing Source verified

    Step-by-step visibility into agent behavior with native framework tracing, OpenTelemetry support, and message threading for multi-turn chat.

  • Production monitoring Source verified

    Real-time dashboards for token usage, latency, error rates, cost breakdowns, and feedback scores with webhook and PagerDuty alerts.

Evaluation

  • Online evaluations Source verified

    Score production traffic with online LLM-as-judge and code evals on selected characteristics.

Analytics

  • Insights and clustering Source verified

    Automatic analysis and clustering of traces to surface usage patterns, common behaviors, and failure modes with executive summaries.

Platform

  • SmithDB trace storage Source verified

    Purpose-built storage for deeply nested agent traces supporting random access, full-text search, JSON path filtering, and trajectory queries.

Integrations

  • Multi-language SDKs Source verified

    SDKs for Python, TypeScript, Go, and Java to trace applications built with OpenAI SDK, Anthropic SDK, Vercel AI SDK, LlamaIndex, or custom code.

Quick start

Trace an OpenAI call with the Python SDK

Install the langsmith package, enable tracing with environment variables from the SDK README, then wrap an OpenAI client so calls are traced automatically.

Trace an OpenAI call with the Python SDK
pip install -U langsmith

import openai
from langsmith.wrappers import wrap_openai

client = wrap_openai(openai.Client())
client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello, world"}]
)

Source: https://pypi.org/project/langsmith/. Examples use placeholders only. Never paste a real key into a profile, config file you share, or a ticket.

MCP support: Current MCP support details were not cleanly verified for Braintrust in this research pass. Check the official Braintrust documentation for the supported setup before wiring an MCP client to it.

Works with

Frameworks

Works with LangChain, LangGraph, OpenAI SDK, Anthropic SDK, Vercel AI SDK, LlamaIndex, and custom implementations, with OpenTelemetry ingestion.

Packages

Python package langsmith on PyPI and TypeScript package langsmith on npm, plus Go and Java SDKs referenced on the product page.

API

Async tracing via SDK callback handler to a distributed collector, with data export and OTel pipeline integration.

Deployment

Managed cloud, bring-your-own-cloud, and self-hosted Kubernetes deployment on Enterprise plans.

Only sourced support is listed. A missing framework means AgentsUse has not verified it yet, not that it cannot work.

Health and maintenance

Package
PyPI: langsmith, version 0.14.4
License
freemium
Maintainer
LangChain

Closed product with no meaningful public product repository, so GitHub stars are omitted. The SDK repository langchain-ai/langsmith-sdk is referenced in search results with 1068 stars, not used as product stars. PyPI version 0.14.4 from a registry release check dated 2026-10-02. Weekly downloads not read, so omitted.

Pricing and license

Freemium model with a free Developer tier, a Plus tier priced per seat per month with included base traces and pay-as-you-go usage beyond that, and custom Enterprise pricing. Usage is metered in LangChain storage and compute units tied to trace volume and retention, as described on the LangChain pricing page.

Official pricing or docs →

Limitations and safety

  • Self-hosted and hybrid deployment are Enterprise-only according to the product FAQ and pricing summaries, while Developer and Plus are cloud-hosted.
  • Pricing combines per-seat fees with per-trace usage and retention upgrades, so cost grows with both team size and trace volume.
  • Deepest zero-config tracing is for LangChain and LangGraph stacks, while other frameworks rely on SDK wrappers or OpenTelemetry instrumentation.
Safety

Browser and data tools can read pages, fill forms, and download files. Start with a test account or read-only access, keep credentials in environment variables, and review agent actions before connecting anything that can spend money, send messages, or delete data.

Alternatives to LangSmith

Common questions

What does LangSmith do for an AI agent?

Agent and LLM observability platform from LangChain for tracing, monitoring, and evaluating applications in production.

Is LangSmith open source?

This profile records the pricing model as freemium. See the pricing section for the sourced summary.

Does LangSmith support MCP?

Current MCP support details were not cleanly verified for Braintrust in this research pass. Check the official Braintrust documentation for the supported setup before wiring an MCP client to it.

Sources and freshness

Last checked 2026-10-07. Verification label: source verified, which means public claims trace to the sources above. It does not mean AgentsUse ran the tool. Spotted an error? Send a correction. Back to the tools directory.