Armature
Armature is analytics and evaluation software for AI agents connected through MCP servers, showing what users actually did and catching regressions when the underlying model changes.
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Description
If you've shipped an AI agent or MCP-connected tool, you've probably hit the wall every team hits: it works in your own testing, but you have no idea what real users are actually asking it to do, whether it's succeeding, or whether it silently got worse the last time OpenAI or Anthropic updated a model. Armature is built to close that blind spot — it records what happens during real agent sessions and turns that into something you can actually look at and act on, instead of guessing.
Technically, Armature captures full session traces through MCP servers, showing user intent, the agent's reasoning steps, and the final outcome, then automatically groups similar use cases and ranks them by success rate so you can spot where things are breaking without reading every transcript by hand. It runs a dedicated eval suite across multiple AI models to catch regressions when you swap models or a provider ships an update, and it strips PII and secrets before anything is stored. SDKs are available for TypeScript, Python, and Go. The free tier includes 1,000 credits a month with 7-day retention; beyond that it's pay-as-you-go at $50 per 1,000 additional credits, with custom plans adding SSO/SAML, audit logs, and longer retention for larger teams.
💬 Our review
The short version: if you're running an AI agent or MCP server in production and currently have zero visibility into what it's actually doing for real users, Armature fills a genuine gap — session replay plus automated eval-on-model-change is exactly the kind of thing that's painful to build in-house but cheap to get wrong without it. The free tier's 1,000 credits are enough to validate whether the tool fits before paying anything.
The honest tradeoff is that this is a young, narrow category — MCP-specific observability — competing against general-purpose LLM observability tools like LangSmith or Helicone that cover a broader range of frameworks, not just MCP. If your stack is MCP-first, Armature's specialization is an advantage; if you're mixing MCP with other agent frameworks, a more general observability tool might avoid vendor lock-in to a single protocol. The 7-day retention on the free tier is also short enough that anything you want to analyze over time will require the paid plan.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Gratuit : 1000 crédits/mois, rétention 7 jours. Payant : 50$ par 1000 crédits supplémentaires. Plans sur mesure avec SSO/SAML, logs d'audit, rétention étendue.
Pros
Replay complet de sessions avec intent, raisonnement et résultat
Regroupement automatique des cas d'usage classés par taux de succès
Suite d'évaluation exécutée sur plusieurs modèles pour détecter les régressions
Rédaction automatique des PII/secrets avant stockage
Cons
Rétention limitée à 7 jours sur le tier gratuit
Spécialisé MCP — moins pertinent si votre stack agent n'est pas MCP-first
Catégorie jeune face à des outils d'observabilité LLM plus généralistes (LangSmith, Helicone)