Dev & Engineering python-sdkagent-runtimerest-apissewebsocketsmcpjwt-rbacopentelemetry

Agno Agent Platform

Build, self-host, and operate agent platforms with an SDK, AgentOS runtime, and control UI.

FollowAgents review · FARS-2.1
Not recommended
41/ 100 5-point scale 2.1 / 5
1 2 3 4 5 6
Per-dimension scores and reasoning
1Trust7 / 29 · 1.2/5

Evidence: README mentions JWT-based RBAC, multi-tenant isolation, human approval, indicating permission control and user confirmation; Telemetry section states it sends telemetry events but never prompts, messages, or outputs, and can be disabled, showing data flow transparency; sensitive data handling has security feature descriptions. Deductions: these are mostly feature claims without implementation details or code evidence; dependency security lacks dependency list or vulnerability scanning; rollback mechanism not mentioned; publisher identity unverified, source attribution only based on repo metadata.

2Reliability6 / 14 · 2.1/5

Evidence: README is consistent, feature list aligns with doc links, good self-consistency; dependency availability: README mentions multiple deployment templates and integrations but no dependency versions or availability guarantees; failure messages: no error handling or user-visible error examples. Deductions: lack of concrete implementation and test evidence, failure messages not documented.

3Adaptability9 / 18 · 2.5/5

Evidence: README clearly targets developers building agent platforms, provides multiple deployment scenarios (Docker, AWS, GCP, etc.) and integrations (Slack, Telegram, etc.), good environment fit; capability boundaries: describes feature scope but no explicit limits; trigger precision: mentions human approval and scheduling but no detailed trigger conditions. Deductions: capability boundaries and trigger precision lack specifics.

4Convention9 / 18 · 2.5/5

Evidence: README structure is clear, includes intro, quick start, features, community, contributing, license, good information architecture; install notes: provides via coding agent or manual, but no direct install command; naming stability: product name and doc links consistent, but no version history; examples and FAQ: provides example links but no FAQ; known limitations not listed; license Apache-2.0, compliant; versioning changelog not provided; maintenance responsibility: contributing guide but no explicit maintainers. Deductions: missing version history, FAQ, known limitations.

5Effectiveness7 / 13 · 2.7/5

Evidence: output usability: README describes production API, storage, observability, diverse output forms; marginal value: provides 100+ integrations and multiple deployment options, high value; cost-benefit: no performance data or cost analysis. Deductions: cost-benefit lacks evidence.

6Verifiability3 / 8 · 1.9/5

Evidence: README feature claims have doc links but no implementation code or test results; cross-source corroboration: multiple deployment templates and doc links but no independent verification; fact-inference separation: README distinguishes feature descriptions and recommendations but does not explicitly mark inferences. Deductions: lack of verifiable tests or independent evidence.

Evidence confidence: Low Reviewed Aug 09, 2026 Reviewed revision d28d580499e4
The upstream repository has new commits since this review. The score still applies to the reviewed revision shown and may not cover the latest changes.
Safety controls not found in source: dependency security, rollback or recovery path
Before you use it
  • Publisher identity unverified, treat source with caution.
  • Dependency security information missing, recommend checking dependency list and vulnerability scanning.
  • Rollback mechanism not mentioned, confirm before deployment.
  • Telemetry is enabled by default, though disableable, be aware of data privacy.
Review evidence [1][2][3][4][5]
See the full review method →

What does this agent do, and when should you use it?

Agno is a framework and runtime for agent platforms, rather than a single-purpose end-user agent. The Agno SDK builds agents, the AgentOS runtime runs the platform as a service, and the AgentOS UI manages it. Its runtime exposes more than 50 endpoints with SSE and WebSocket support for product-facing integrations. The platform can store sessions, memory, knowledge, and traces in your own database, with OpenTelemetry tracing, run history, and audit logs. It suits teams that need control over data, memory, and JWT-based RBAC while deploying containerized services on Docker, Railway, AWS, GCP, or similar environments.

Developers build agents with the Agno SDK and run the resulting platform as a service through the AgentOS runtime. The runtime exposes more than 50 endpoints with SSE and WebSocket support, and can store sessions, memory, knowledge, and traces. Pre-built toolkits connect to GitHub, Slack, Postgres, and other services; Context Providers can access live data from Slack, Drive, wikis, MCP, or custom sources. It can pause runs for human confirmation and block tools that need administrator approval, while the AgentOS UI is used to manage the platform.

  1. A product engineering team that needs to expose internally built agents through REST-style APIs, SSE, or WebSockets.
  2. An enterprise team that needs sessions, memory, knowledge, and traces stored in its own database.
  3. An internal-tools team connecting agents to GitHub, Slack, or Postgres while sourcing context from Slack, Drive, wikis, or MCP.
  4. An organization that needs JWT-based RBAC, multi-user and multi-tenant isolation, plus audit logs around agent activity.
  5. A platform team deploying agent services with Docker, Railway, AWS, GCP, or another container-capable environment.

What are this agent's strengths and limitations?

Pros
  • Separates agent construction, service execution, and platform management across the Agno SDK, AgentOS runtime, and AgentOS UI.
  • Offers more than 50 SSE- and WebSocket-capable API endpoints for building product-facing agent experiences.
  • Keeps sessions, memory, knowledge, and traces in your own database while adding OpenTelemetry tracing, run history, and audit logs.
  • Documents JWT-based RBAC, multi-user and multi-tenant isolation, human approval, and administrator approval controls.
Limitations
  • The supplied material lacks package installation commands, minimal code, authentication setup, and endpoint examples, so technical evaluation requires additional documentation.
  • The documented local route uses Docker and includes Postgres storage, creating runtime and data-operation responsibilities for adopters.
  • Integrations, context sources, permission policies, and tenant isolation need environment-specific configuration; default behavior is not established here.
  • A telemetry event is sent for each agent run; the material says prompts, messages, and outputs are excluded, but opting out requires AGNO_TELEMETRY=false.

How do you install or deploy this agent?

The supplied material does not provide an Agno SDK package-install command, version requirements, credential setup, or minimal runnable code. Its documented getting-started route is to have Claude Code, Cursor, or Codex clone agno-agi/agentos-railway into a folder named agent-platform, enter that folder, read its README, and follow its getting-started guide; this runs the platform locally with Docker. For another deployment target, the material names agentos-docker, agentos-aws, agentos-gcp, agentos-azure, agentos-fly, agentos-render, agentos-modal, and agentos-helm as alternatives.

How do you use this agent?

Build agents with the Agno SDK, run the platform as a service with the AgentOS runtime, and manage it through the AgentOS UI. Integrate a product through the runtime API, whose endpoints are documented as supporting SSE and WebSockets. Configure pre-built toolkits or Context Providers when external systems or live context are needed, and enable human approval for sensitive actions. The supplied material does not specify SDK calls, endpoint paths, credential formats, or a first request example.

How does this agent compare with similar options?

The README presents agentos-railway, agentos-docker, agentos-aws, agentos-gcp, agentos-azure, agentos-fly, agentos-render, agentos-modal, and agentos-helm as starter templates that differ in deployment scripts while otherwise remaining identical. They are deployment-entry alternatives, not competing products.

FAQ

Does telemetry send prompts or model outputs?
The material says an event is sent for every agent run, but prompts, messages, and outputs are never sent. Set AGNO_TELEMETRY=false to disable telemetry.
Can we retain platform data in our own infrastructure?
Yes. The material states that sessions, memory, knowledge, and traces can be stored in your own database, and emphasizes control over data, memory, and security posture.
Which actions can require approval?
Human approval can pause a run for user confirmation, and tools requiring administrator approval can be blocked.
Do we need to deploy it ourselves?
It can run locally with Docker or be deployed using templates for Railway, AWS, GCP, Azure, Fly, Render, Modal, or Helm. Those targets need an environment capable of running containers.

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