Monitoring Tools for AI Agents
Track application performance, uptime, and health. Agents can self-diagnose and respond to incidents.
31 tools in this category
AgentOpsMCP
Session replay, monitoring, and evaluation for AI agents
Arize PhoenixMCPCLI
Open-source tracing and evaluation for LLM applications
AxiomCLI
Cloud-native logs, traces, and event data for agent systems
Baserun
Observability, testing, and evaluations for LLM applications
BentoLabs AI
Monitoring and learning for long-running AI agents
BraintrustMCPCLI
Evaluation, tracing, and prompt management for AI products
Confident AIMCPCLI
Evaluation and observability platform for reliable AI agents
CovalMCPCLI
Simulation, evaluation, and monitoring for voice and chat agents
Credal.aiMCPCLI
Security and governance control plane for enterprise agents
Galileo
AI observability and evaluations for reliable production agents
GolfMCPCLI
Security and governance infrastructure for MCP tools
Guardrails AICLI
Open-source validation framework for safer, structured LLM applications
HeliconeMCP
Open-source AI gateway and observability platform
Kestrel AIMCPCLI
Deterministic platform-engineering workflows built and operated by AI agents
LaminarMCPCLI
Tracing, evaluations, and debugging for AI agents
LangfuseMCPCLI
Open-source LLM engineering platform: traces, evals, and prompts
LangSmith
Framework-agnostic tracing, evaluation, and monitoring for agents
LemmaMCP
Production tracing and debugging for AI agents
LiteLLMMCPCLI
Open-source gateway for calling 100+ LLM APIs
OpenlayerCLI
Evaluation, observability, and governance for production AI
Parea
Evaluation and observability for LLM applications and agents
PortkeyMCPCLI
AI Gateway for 1600+ LLMs — observability, guardrails, and governance in one platform
PostHogMCPCLI
Product analytics and observability for agent experiences
PromptfooCLI
Open-source evaluations and red teaming for LLM applications and agents
Respan
AI gateway, evaluations, and observability for agents
SentryMCPCLI
Full-stack error, performance, and AI agent monitoring
Superagent
Security scans, guardrails, and red teaming for AI-native software
TensorZeroCLI
Open-source gateway, observability, and optimization stack for LLM applications
Traceloop
OpenTelemetry observability for LLM and agent applications
Agent-Ready Repo Auditor
Public-repository evidence checks for coding agents
Telemetry
Structured events and SQL for coding agents
How to compare Monitoring tools
Track application performance, uptime, and health. Agents can self-diagnose and respond to incidents. Start by writing down the action the agent must complete, the data it may access, and the evidence an operator needs after the run. Those requirements are more useful than comparing long feature lists without a workload.
Test two or three providers with the same input set. Compare output quality, latency, error behavior, authentication, SDK fit, usage limits, and total cost at the expected volume. Verify whether retries are safe and whether the service exposes enough logs or identifiers to investigate a failed agent run.
4agent does not treat inclusion as an endorsement. Listings summarize public integration details and link to each provider so you can confirm current documentation, pricing, regional availability, data handling, and service terms before adoption.
Sources and verification
Use these primary sources to verify current behavior before making an implementation or purchasing decision. Product capabilities, limits, and prices can change after a 4agent listing is reviewed.