Low Risk

premium_ai_company

Get the per-ticker AI intelligence envelope for one AI bellwether: latest 10 SEC filings, latest 10 AI-tagged news mentions filtered by curated aliases, strategic and equity funding rounds where the company is a lead or notable investor, and cohort metadata. One call replaces four free siblings (...

Part of the TensorFeed server.

premium_ai_company is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call premium_ai_company 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 premium_ai_company 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "premium_ai_company": {}
  }
}

See the full TensorFeed policy for all 79 tools.

Get this rule live on your own TensorFeed server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access premium_ai_company gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so premium_ai_company only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the premium_ai_company tool do? +

Get the per-ticker AI intelligence envelope for one AI bellwether: latest 10 SEC filings, latest 10 AI-tagged news mentions filtered by curated aliases, strategic and equity funding rounds where the company is a lead or notable investor, and cohort metadata. One call replaces four free siblings (sec/filings, news, funding, cohort) plus the agent-side alias filter. Costs 1 credit ($0.02). Strict-premium; ticker must be in the cohort.. It is categorised as a Read tool in the TensorFeed MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on premium_ai_company? +

Register the TensorFeed MCP server in PolicyLayer and add a rule for premium_ai_company: 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.

What risk level is premium_ai_company? +

premium_ai_company is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit premium_ai_company? +

Yes. Add a rate_limit block to the premium_ai_company 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.

How do I block premium_ai_company completely? +

Set action: deny in the PolicyLayer policy for premium_ai_company. 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.

What MCP server provides premium_ai_company? +

premium_ai_company 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.

Enforce policy on every TensorFeed tool call.

Deterministic rules across all 79 TensorFeed tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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