Cadenya vs Moxie Docs: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Cadenya and Moxie Docs — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Cadenya

Paid

A managed agent runtime that layers your tools, agents and objectives so teams can test agent behavior safely and iterate fast.

Unified Tool Layer: Connect MCP servers, OpenAPI specs and existing endpoints once, and expose them to every agent through a single managed interface.
Model-Agnostic Variations: Set a default model and run canary variations on other providers side by side to compare behaviors before promoting a change.
Progressive Tool Discovery: Tool schemas stay out of the context window until an agent asks for them, with configurable max tools per search, search hints and a rerank threshold, so every request gets smaller.
Live Token Metering: Track cost as it accrues across loops, active variations, memory entries and widgets, so usage is visible rather than discovered on the invoice.
Webhooks and SSE Streaming: Push agent events — assistant messages, tool results, approval requests, sub-agent spawns, compaction, timeouts — into your own apps in real time.
Memory Layers: Attach stored documents such as playbooks and policy sets to an agent so its guidance persists across objectives.
Outcome Feedback Scoring: Collect scored comments on each objective, attributed to the variation and model that produced it, to see which behaviors actually work.
Embeddable Widgets: Drop an agent experience into any frontend as a widget rather than building the conversational surface yourself.

Operational Exception Handling: Run an agent that detects stalled shipments or orders and reroutes them through your dispatch API within policy.
Safe Model Migration: Evaluate a new frontier model as a canary variation against live objectives before switching the default.
Wrapping Existing APIs: Turn internal OpenAPI endpoints into agent-callable tools without rewriting the services behind them.
Embedding Agent Chat in a Product: Ship a conversational agent surface into an existing frontend using widgets instead of building it in-house.
Cost Control at Scale: Use progressive discovery and live metering to keep context size and per-loop cost down as agent traffic grows.
Agent Quality Review: Compare scored feedback across variations to understand which prompt or model changes improved real outcomes.

jackalope.digital

Freemium

Moxie Docs indexes your GitHub repos, generates convention-grounded docs, detects doc drift on every merge, and serves an MCP for coding agents.

Merge-triggered Re-indexing: Every merge triggers a fresh index pass so documentation stays synchronized with the current state of the repo.
Grounded Convention Docs: Generates architecture and convention documentation grounded in the actual source, with deep symbol and import-graph analysis for TypeScript, JavaScript, and Python.
Documentation Drift Detection: Flags pages affected by code changes and regenerates stale documentation with cited diffs so reviewers see what changed and why.
Friday Cleanup PRs: Pro and Team plans automatically open weekly docs-only pull requests so keeping docs current becomes a bounded review, not a rewrite project.
MCP Context Server: Exposes an MCP server so Cursor, Claude Code, and Codex pull verified conventions from Moxie instead of re-crawling the repo each session.
Free Browser-based Doc Utilities: README, AGENTS.md, ADR, .cursorrules, CLAUDE.md, .windsurfrules, Mermaid, SQL-to-ER, and llms.txt generators run in the browser with no account.
Scoped GitHub App: Access is scoped to the repos you select, tokens are encrypted server-side, and code is used only to generate documentation and MCP context.
Broad Language Support: Documentation and search work on any GitHub repo, with recognition for TypeScript, JavaScript, Python, Go, Rust, Ruby, Java, PHP, SQL, Svelte, Vue, Kotlin, Swift, Elixir, and Zig.

Automating living docs: Point Moxie at a private repo so architecture and convention docs stay grounded in the current code without manual rewrites.
Feeding Cursor and Claude Code: Connect the MCP server so coding agents pull verified conventions from Moxie instead of re-crawling the codebase.
Onboarding new engineers: Give a new hire a searchable, always-fresh guide to the codebase with symbol and import-graph context.
Catching doc drift on merge: Fail loudly when a merged PR leaves documentation stale, with cited diffs pointing to what needs to change.
Weekly docs cleanup review: Merge the Friday Cleanup PR each week to keep documentation current as a bounded, review-only workflow.
One-off doc generation: Use the free browser-based generators to draft an AGENTS.md, CLAUDE.md, or llms.txt without signing up.
SQL data-model diagrams: Paste CREATE TABLE SQL to get a live Mermaid ER diagram and optional AI data-model docs.
Cursor Rules authoring: Draft a structured .cursorrules file with live preview and shareable export.