Agno vs TradingAgents

Agno

An Apache 2.0 Python agent framework at 3.1.1 with an MCP client, tool confirmation and admin approvals, a durable job queue and 25 stable releases in 90 days. Usage telemetry is on by default with unhashed identifiers, and three high or critical advisories were published against it in the last 12 months, all fixed.

TradingAgents

An Apache 2.0 LangGraph framework at 0.7.0 with six releases in 90 days, a dated changelog with upgrade notes, a public test matrix and point-in-time rules for historical runs. It has no MCP client or server, no PyPI package and no documentation beyond the README, and its output is a model-written rating that places no orders.

Agno

1. Set AGNO_TELEMETRY=false before the first run, and pass telemetry=False to AgentOS and to each eval, which ignore the variable
2. Configure JWT_VERIFICATION_KEY with AgentOS authorisation switched on, or OS_SECURITY_KEY, before exposing AgentOS. With neither set, REST and MCP routes take no credential
3. Mark tools that write with requires_confirmation, and resume with continue_run once every requirement is resolved
4. Set tool_call_limit on agents. The default is None
5. Install extras for what you use, such as agno[mcp] for MCPTools and agno[os,mcp] for AgentOS with its MCP server

TradingAgents

1. Run headless with tradingagents --ticker <T> --date <YYYY-MM-DD> --analysts market,news,fundamentals --save --no-show; a missing answer stops the run and names the flag
2. Guard on the REVIEW signal before mapping propagate()'s decision to a rating; it means no rating could be parsed
3. Set SEC_EDGAR_USER_AGENT to the operator's own name and address before fetching US fundamentals
4. Keep provider keys out of the working directory tree unless intended, since the package loads the nearest .env on import
5. Treat the rating as model output for research; the framework places no orders and its results vary between runs