{"id":"helicone-api","name":"Helicone API","homepage":"https://helicone.ai","repo_url":"https://github.com/Helicone/helicone","category":"developer-tools","subcategories":["observability","llm-monitoring","ai-infrastructure"],"tags":["llm-observability","monitoring","logging","openai-proxy","cost-tracking","caching","agent-monitoring"],"what_it_does":"Helicone is an LLM observability and proxy platform. Drop one header into any OpenAI (or Anthropic, Azure, Mistral, etc.) API call and all requests are logged, analyzed, and monitored. Features include: request/response logging, cost tracking, latency monitoring, user-level analytics, prompt management and versioning, A/B testing, smart caching (LLM semantic cache), rate limiting, and custom dashboards. Supports agent tracing with session IDs and custom properties for debugging multi-step agent workflows.","use_cases":["Monitoring LLM API costs across all providers from a single dashboard","Debugging failed agent runs by replaying exact prompts and responses","Tracking LLM latency and error rates in production agent systems","Implementing semantic caching to reduce duplicate LLM API costs","User-level usage tracking and quota enforcement in multi-tenant AI apps","Prompt versioning and A/B testing to measure prompt quality improvements","Session-based tracing of multi-step agent workflows for debugging"],"not_for":["Teams that cannot route LLM traffic through a third-party proxy for security/compliance reasons","Local development without internet access","Non-LLM API monitoring (use Datadog or similar for general API monitoring)"],"best_when":"You're running LLM-powered agents in production and need visibility into costs, errors, and performance. The proxy-based architecture means zero code changes beyond adding one header — just change your base URL and add the Helicone-Auth header.","avoid_when":"You cannot accept a proxy in your LLM call path for latency or compliance reasons, or your compliance requirements prohibit routing API responses through third parties.","alternatives":[{"id":"langsmith-api","reason":"LangSmith focuses on LangChain-native tracing with richer agent workflow visualization; Helicone is provider-agnostic and works with any LLM API"},{"id":"wandb-api","reason":"W&B is better for ML experiment tracking; Helicone is better for production LLM API monitoring"}],"af_score":83.5,"security_score":null,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"current","last_evaluated":"2026-03-01T09:50:05.677341+00:00","performance":{"latency_p50_ms":20,"latency_p99_ms":100,"uptime_sla_percent":99.9,"rate_limits":"Proxy adds ~5-20ms latency overhead per call. No rate limits on the proxy itself — limits are enforced by the underlying LLM API.","data_source":"llm_estimated","measured_on":null}}