Register a free webhook subscription. TensorFeed POSTs HMAC-signed deliveries to your callback_url when the watch spec fires (price drop, status change, leaderboard rank shift, macro indicator threshold crossing, etc). 5 watches per IP, 25 fires per watch, 30-day TTL. Same delivery infrastructure...
AI agents use register_free_watch to create or update resources in TensorFeed — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your TensorFeed environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
spec | object | Yes | Watch spec. Examples: { type: "price", model: "opus-4-7", field: "blended", op: "lt", threshold: 50 }; { type: "status", provider: "openai", op: "becomes", valu |
secret | string | — | Optional shared secret for HMAC-SHA256 signing. If omitted, TensorFeed generates a 32-hex secret and returns it once. |
fire_cap | number | — | Optional cap on total fires for this watch. Capped at 25 for free tier; smaller values honored. |
callback_url | string | Yes | HTTPS URL to receive POST deliveries. Must NOT be private/localhost (SSRF guarded). |
Parameters from the server's own tool schema.
This is primarily a Write operation: it creates a new webhook subscription resource and stores configuration state (watch spec, callback_url, secret, TTL). The tool does not delete, move money, or execute arbitrary code. While it does POST to external URLs, those are automated notifications triggered by the watch spec conditions—the tool itself is not executing user-supplied code or shell commands.
From the tool's definition Tool 'registers' a webhook subscription and 'TensorFeed POSTs' deliveries to a callback_url, creating a persistent resource with state (5 watches per IP, 30-day TTL, secret management).
Risk signalsAccepts URL/endpoint input (callback_url) · Handles credentials or secrets (secret)
Attacks that exploit this kind of access
Register a free webhook subscription. TensorFeed POSTs HMAC-signed deliveries to your callback_url when the watch spec fires (price drop, status change, leaderboard rank shift, macro indicator threshold crossing, etc). 5 watches per IP, 25 fires per watch, 30-day TTL. Same delivery infrastructure as paid /api/premium/watches. If you omit secret, TensorFeed generates one and returns it; you cannot retrieve it again later. Same IP for management; manage via the REST endpoints under /api/watches/free/{id}. It is categorised as a Write tool in the TensorFeed MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
register_free_watch accepts 4 parameters: spec, secret, fire_cap, callback_url. Required: spec, callback_url. The full parameter table on this page comes from the server's own tool schema.
Register the TensorFeed MCP server in PolicyLayer and add a rule for register_free_watch: 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.
register_free_watch is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the register_free_watch 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 register_free_watch. 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.
register_free_watch 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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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