Langtrace
Open-source LLM observability platform that traces calls to LLM APIs (OpenAI, Anthropic, etc.) and provides evaluation, cost tracking, and performance analytics.
Evaluated Mar 06, 2026
(0d ago)
vcurrent
⚙ Agent Friendliness
60
/ 100
Can an agent use this?
🔒 Security
82
/ 100
Is it safe for agents?
⚡ Reliability
78
/ 100
Does it work consistently?
Score Breakdown
⚙ Agent Friendliness
MCP Quality
--
Documentation
82
Error Messages
78
Auth Simplicity
90
Rate Limits
75
🔒 Security
TLS Enforcement
100
Auth Strength
80
Scope Granularity
70
Dep. Hygiene
82
Secret Handling
80
API key has no scope restrictions; self-hosted gives full data control
⚡ Reliability
Uptime/SLA
80
Version Stability
78
Breaking Changes
75
Error Recovery
78
Best When
Building multi-model LLM applications and needing visibility into per-call costs, latency, and quality across providers.
Avoid When
Your LLM usage is simple single-provider with no evaluation requirements — basic logging suffices.
Use Cases
- • Auto-trace all OpenAI and Anthropic API calls to track token usage, latency, and costs
- • Evaluate LLM response quality with built-in and custom evaluators on production traces
- • Compare model performance across different LLM providers side-by-side using trace datasets
- • Alert on LLM latency spikes or cost anomalies with threshold-based monitoring
- • Export traces as datasets for fine-tuning or prompt optimization workflows
Not For
- • General application monitoring beyond LLM calls — use Datadog APM or Honeycomb
- • Self-hosted deployment with zero external data egress requirements (cloud mode required)
- • Real-time streaming trace analysis — traces are batched for ingestion
Interface
REST API
Yes
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
No
Authentication
Methods:
OAuth: No
Scopes: No
LANGTRACE_API_KEY environment variable; one key per project
Pricing
Model: freemium
Free tier:
Yes
Requires CC:
No
Open source — can self-host with full features
Agent Metadata
Pagination
cursor
Idempotent
No
Retry Guidance
Not documented
Known Gotchas
- ⚠ Auto-instrumentation patches LLM client libraries at import time — import order matters; import langtrace before openai/anthropic
- ⚠ Cloud free tier 10K trace limit resets monthly but does not warn at 80% usage — monitor manually
- ⚠ Evaluation scores are computed async after trace ingestion — not available synchronously in response
- ⚠ Self-hosted requires PostgreSQL + ClickHouse for full feature parity — not just a single Docker container
- ⚠ SDK wrapping may add 5-20ms overhead to LLM calls — benchmark in latency-sensitive applications
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Langtrace.
$99
Scores are editorial opinions as of 2026-03-06.