Brain Memory
Free · Open source
Long-term continuity in multi-session coding projects
Cadenya
PaidAPIAgentic
Every agent runtime looks clean in the demo — the problems show up when you need to swap a model without breaking behavior, or test a canary variation without touching production.
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Screenshots 4
Summary
Cadenya is an agent runtime built around a layered model: tools connect once through MCP, OpenAPI specs, or existing endpoints; agents carry assigned tool sets, memory layers, and system prompts; objectives dispatch into a loop. The variation system is the differentiating structure — you run a canary agent against a different model or tool assignment alongside your default, compare scored feedback per objective, and promote or discard without touching infrastructure. Progressive tool discovery keeps full tool schemas out of the context window until the agent asks, which means fewer tokens consumed per request. The ceiling appears when your logic needs branching that the runtime does not expose as a configurable primitive — teams building conditional pipelines will reach that wall before teams running single-agent dispatch loops.
Bottom line: Cadenya fits teams that need safe model-swapping and side-by-side variation testing on a real agent; it does not fit teams whose next feature is conditional branching between agents based on what the prior step returned.
Pricing Plans
Subscription- Price
- $20 minimum monthly
Minimum
$20per month
Base paid access with Development and Production workspaces
- API access
- CLI
- OpenRouter $5 starter key
View full pricing on cadenya.com →
Pricing may have changed since last verified. Check the official site for current plans.
Find your fit
Before you choose Cadenya
More options in Agent Frameworks. Compare pricing, platforms, and features side by side.
Agent-Talk
Free · Open source
Cross-model agent collaboration
Pros
- Variation-level model assignment with per-objective scored feedback, so you can compare Claude against GPT on the same real workload before committing to either — without running a separate test environment.
- Tool schemas stay out of the context window until the agent retrieves them by search, so token consumption scales with what the agent actually needs rather than the full size of your tool library.
- MCP servers, OpenAPI specs, and existing endpoints all connect through the same tool layer, which means adding a new integration does not require rebuilding the agent that uses it.
- Webhook delivery covers granular agent events — tool approval requests, sub-agent spawning, timeouts — so downstream applications stay in sync without polling.
- Tool approval gates surface as a first-class event type, so teams that need to review before an agent calls an external system can intercept at the right moment without building that interception themselves.
Cons
- Cadenya has no self-hosted option — teams with data residency requirements or policies that prohibit sending workload to a third-party cloud runtime cannot deploy this at all, and the next step is evaluating open-source runtimes that ship a self-hosted binary.
- The runtime's documented primitives are tools, agents, and objectives; conditional branching based on what one step returns is not described as a configurable feature. Teams whose second or third agent needs to route based on parsed output from the first will add their own orchestration layer on top, which means maintaining logic in two places.
- There is no free tier — the vendor states a minimum $20 fee — so teams evaluating fit before committing to spend cannot prototype at zero cost, which pushes evaluation toward competitors that offer a free usage band.
About
- Platforms
- Web, CLI (macOS, Windows)
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- September 14, 2026
Best For
Who it's for
- Developers building agentic workflows
- Teams needing tool approval and context management
- Users integrating custom LLM providers
What it does well
- Dispatching objectives to agents with assigned tools
- Managing isolated workspaces for development and production
- Integrating OpenAPI-based tools into agent variations
Integrations
Frequently Asked Questions
- Is Cadenya free?
- Cadenya is a paid tool ($20 minimum monthly). No permanent free tier is offered.
- Does Cadenya have an API?
- Yes. Cadenya exposes a developer API. See the official documentation at https://cadenya.com for details.
- What platforms does Cadenya support?
- Cadenya is available on: Web, CLI (macOS, Windows).
Curated lists that include this category
Swapping models or testing variations breaks production runs
The summary lead states that every agent runtime looks clean in the demo, yet problems appear when swapping a model without breaking behavior or testing a canary variation without touching production. Cadenya addresses this through a layered model where tools connect once via MCP, OpenAPI specs, or existing endpoints. Agents receive assigned tool sets, memory layers, and system prompts, then objectives run in a loop. The variation system lets users run a canary agent against a different model or tool assignment alongside the default, compare scored feedback per objective, and promote or discard changes without infrastructure changes.
Progressive discovery and unified connections
Progressive tool discovery keeps full tool schemas out of the context window until the agent requests them by search, so token use scales with actual needs rather than the full library size. MCP servers, OpenAPI specs, and existing endpoints all feed the same tool layer, so new integrations do not require rebuilding agents. The vendor states support for OpenRouter, OpenAPI tools, and custom LLM providers plus a CLI on macOS and Windows.
Price starts at a $20 minimum monthly subscription. The docs describe primitives limited to tools, agents, and objectives with no documented support for conditional branching based on step output.
Who it is for / who should skip it
Best for developers building agentic workflows and teams needing tool approval and context management or custom LLM provider integration. Skip it if data residency rules block third-party cloud runtimes or if teams require self-hosted binaries and complex branching logic without adding external orchestration.
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