TensorFeed's daily scan of new repositories across the AI agent ecosystem (Anthropic, OpenAI, Microsoft, ModelContextProtocol, HuggingFace, LangChain, frontier-lab orgs) plus recent MCP, x402, and skill keyword sweeps. Eleven signals total, deduped + composite-scored (signal_weight × log10(stars+...
Part of the TensorFeed server.
Free to start. No card required.
AI agents call get_agent_opportunities to retrieve information from TensorFeed without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though get_agent_opportunities only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"get_agent_opportunities": {}
}
}See the full TensorFeed policy for all 79 tools.
These attack patterns abuse exactly the kind of access get_agent_opportunities gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
TensorFeed's daily scan of new repositories across the AI agent ecosystem (Anthropic, OpenAI, Microsoft, ModelContextProtocol, HuggingFace, LangChain, frontier-lab orgs) plus recent MCP, x402, and skill keyword sweeps. Eleven signals total, deduped + composite-scored (signal_weight × log10(stars+1) × recency decay) with per-signal MIN/MAX caps so smaller signals are never starved. Refreshed daily at 13:30 UTC. Useful for surfacing distribution targets, integration ideas, or a daily brief on what's launching across the agent space. Free, no auth.. It is categorised as a Read tool in the TensorFeed MCP Server, which means it retrieves data without modifying state.
Register the TensorFeed MCP server in PolicyLayer and add a rule for get_agent_opportunities: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches TensorFeed. Nothing to install.
get_agent_opportunities is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_agent_opportunities rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for get_agent_opportunities. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
get_agent_opportunities is provided by the TensorFeed MCP server (https://mcp.tensorfeed.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 79 TensorFeed tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.