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Armature

Measure whether coding agents choose your product and how its tools perform

Pricing
Free-start option for usability tools; discoverability service and paid pricing require contacting the team
Free plan
Free start advertised without a credit card; ongoing allowance not publicly specified
Platforms
Web dashboard, SDK integration, MCP and CLI testing

Tool Information

Armature
Armature
Updated: September 2026
Tool type: Coding-Agent Discoverability And MCP Evaluation Platform
Pricing: Free-start option for usability tools; discoverability service and paid pricing require contacting the team
Free plan: Free start advertised without a credit card; ongoing allowance not publicly specified
Platforms: Web dashboard, SDK integration, MCP and CLI testing
Login required: Yes for dashboards and configured analytics
API: MCP analytics SDK and evaluation integrations advertised; general public API details not verified
Browser extension: No official browser extension verified
Mobile app: No official native mobile app verified
AI models: Evaluates coding agents such as Claude Code Codex and Cursor; underlying analysis models not publicly specified
Developer: Armature

About Armature

Armature is a platform and service for companies whose products need to be discovered and used by coding agents. It examines two different problems: whether an agent chooses a tool while building something, and whether the tool works reliably once an agent tries to use it. This makes it relevant to API businesses, MCP server developers and teams responsible for developer adoption.

Discoverability in realistic tasks

The discoverability service runs coding agents inside a panel of repositories representing different languages, stacks and constraints. A product counts as selected when the agent installs and connects it in the repository, not merely when its name appears in an answer. Armature uses these runs to identify obstacles in documentation, installation and search presence, then proposes changes for the customer's team to review and ship. The tests run on Armature's infrastructure rather than directly inside the customer's production accounts.

Understanding actual tool use

MCP Analytics reconstructs sessions so teams can inspect sequences of calls, user intent and points of failure. Sessions are grouped into use cases and issues, with replays providing more detail than an aggregate request count alone. The evaluation offering extends this approach to MCP and CLI workflows, replaying scenarios on releases or scheduled runs to detect regressions. These tools help separate a discoverability problem from a product-usability problem.

Working with the results

The usability side is presented as self-serve, using a small SDK on the MCP server, while discoverability is a collaborative service. A developer-tool company can begin with a narrow workflow, establish a baseline and compare results after a documentation or installation change. Armature's reported agent-selection rates are measurements under its test setup, not guaranteed market-wide adoption. The useful question is whether the same representative tasks improve consistently and whether real usage shows fewer failures. Public pricing details are limited, so teams should confirm allowances and service scope before treating the free-start option as an unlimited production plan.

Key features
  • Repository-based coding-agent discovery tests.
  • Measurement of installed and connected product picks.
  • Documentation and installation improvement service.
  • MCP session reconstruction and replays.
  • Use-case and issue grouping.
  • MCP and CLI regression evaluations.
  • Category leaderboards and published methodology.
Use cases
Measuring agent adoption,Improving developer documentation,Finding MCP workflow failures,Testing CLI changes,Comparing agent behavior across repositories
How to use
  1. Choose discoverability or usability as the initial focus.
  2. Create an account or discuss the service with the team.
  3. Provide public product documentation for discovery work.
  4. Install the analytics SDK if inspecting an MCP server.
  5. Select representative tasks and workflows.
  6. Review session traces or repository test results.
  7. Approve and implement relevant product or documentation fixes.
  8. Rerun the same scenarios after changes.
  9. Compare measured improvements with actual product usage.
Best for
Developer Tool Companies, MCP Builders, API Product Teams, Developer Relations Teams
Integrations
MCP server SDK,CLI evaluation workflows,Claude Code,Codex,Cursor
Commercial use
Designed for commercial developer-product evaluation and discovery improvement under agreed service terms

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