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Integration collection

AI agent and LLM integrations

Compare implementation guides for model providers, agent frameworks, tool orchestration, retrieval systems, and AI application runtimes.

Reviewed by the Telemetry product team on . We checked where the code runs, shared event fields, verification steps, and the linked implementation guides. Who reviews this page

20 implementation guides

Every guide includes a server-side snippet, delivery and privacy boundaries, a verification query, related SQL, and links to upstream documentation.

Browse guides

Selection framework

Log where the final result is known

Record the result where the task finishes

Use the model SDK guide for request cost and latency, then add the agent or framework guide where tool selection, retries, and final task status become known.

Keep traces and outcomes distinct

Keep detailed spans in your trace backend. Send the final result to Telemetry with an approved identifier to link it to the trace.

Measure value beside cost

Connect tokens and latency to reviewed outcomes such as accepted, saved, resolved, escalated, or handed off instead of optimizing request volume alone.

Shared event contract

Use the same field definitions across services

  • run_id, feature, provider, model, and status
  • input_tokens, output_tokens, estimated_cost_usd, and latency_ms
  • tool_name, retry_count, cache_hit, reviewer_outcome, and human_handoff

Adapt these fields to your workflow. Document units, allowed statuses, and identifiers before several services write to the same table. Name the team responsible for the schema.

Verification

Exercise failure paths before alerts

  1. 1Run one successful model request and reconcile provider-reported tokens.
  2. 2Exercise one tool failure, retry, and final agent outcome.
  3. 3Confirm raw prompts, completions, credentials, and private tool payloads are excluded.
  4. 4Query cost, latency, failure rate, and accepted outcomes by feature.

Implementation guides

Match the framework, provider, or runtime

Setup guide with source links

OpenAI agent telemetry

Log OpenAI agent runs, tool calls, model usage, latency, cost, and final outcomes with structured events.

Open guide
Setup guide with source links

OpenAI Responses API telemetry

Measure OpenAI Responses API latency, token usage, tool activity, failures, and downstream outcomes without collecting prompts or generated content.

Open guide
Setup guide with source links

LiteLLM gateway and SDK telemetry

Track LiteLLM provider routing, retries, fallbacks, token usage, latency, cost estimates, and accepted outcomes across a controlled model gateway.

Open guide
Setup guide with source links

Anthropic Claude API telemetry

Track Claude API token usage, model, latency, stop reason, errors, cost context, and reviewed product outcomes without storing prompts.

Open guide
Setup guide with source links

Google Gemini API telemetry

Track Gemini request latency, model usage, tokens, finish reason, errors, and reviewed product outcomes without storing prompts or generated content.

Open guide
Setup guide with source links

Amazon Bedrock model telemetry

Measure Bedrock Converse requests by model or inference profile, token usage, latency, stop reason, retries, and business outcome.

Open guide
Setup guide with source links

Azure OpenAI Responses telemetry

Track Azure OpenAI deployment usage, token cost, latency, failures, and product outcomes with editable SQL-ready events.

Open guide
Setup guide with source links

Vercel AI SDK telemetry

Track streaming completions, token usage, retries, latency, and accepted results from AI SDK workflows.

Open guide
Setup guide with source links

LangChain agent outcome telemetry

Connect LangChain agent runs and tool outcomes to product-facing cost, reliability, handoff, and acceptance metrics without duplicating raw traces.

Open guide
Setup guide with source links

LangGraph agent observability

Measure LangGraph run outcomes, node and tool failures, retries, checkpoints, human handoffs, latency, and reviewed task quality.

Open guide
Setup guide with source links

Claude Agent SDK telemetry

Track Claude Agent SDK run outcomes, duration, tool activity, turns, cost, and approved product signals without storing prompts or tool payloads.

Open guide
Setup guide with source links

Pydantic AI agent telemetry

Measure Pydantic AI run outcomes, validated outputs, retries, tool activity, latency, usage, and product acceptance with safe structured events.

Open guide
Setup guide with source links

CrewAI workflow telemetry

Track CrewAI crew and flow outcomes, task counts, handoffs, retries, latency, cost, and accepted results without retaining agent conversations.

Open guide
Setup guide with source links

Google ADK agent telemetry

Measure Google Agent Development Kit sessions, run outcomes, tool activity, handoffs, latency, and approved product signals with SQL-ready events.

Open guide
Setup guide with source links

Mastra agent telemetry

Track Mastra agent and workflow outcomes, tool activity, latency, retries, cost, and product acceptance alongside built-in traces and evals.

Open guide
Setup guide with source links

LlamaIndex agent telemetry

Track LlamaIndex agent and workflow outcomes, tool activity, latency, retrieval versions, cost, and reviewed quality with structured events.

Open guide
Setup guide with source links

DSPy program evaluation telemetry

Measure DSPy program latency, failures, metric scores, optimizer versions, model cost, and accepted outcomes across releases with SQL-ready events.

Open guide
Setup guide with source links

AutoGen task flow, state, and timeout monitoring

Track AutoGen task-flow state, timeouts, team and agent outcomes, tool activity, handoffs, latency, failures, cost, and releases with compact structured events.

Open guide
Setup guide with source links

Semantic Kernel agent telemetry

Measure Semantic Kernel function and agent outcomes, tool activity, model usage, latency, cost, and releases alongside OpenTelemetry traces.

Open guide
Setup guide with source links

MCP server and tool telemetry

Track Model Context Protocol tool outcomes, latency, errors, approvals, retries, clients, and releases without storing arguments or returned content.

Open guide

Verify one end-to-end workflow first

Create a free API key, choose the closest runtime guide, and send one known success and failure before expanding coverage.

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