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tengu_v3_features_catalogue

FEATURE-STORE CATALOGUE — the derived research panels this platform computes for its own models: what exists, how much of it there is, how far back it goes, and how fresh it actually is. Every entry carries MEASURED coverage (rows, symbols, distinct observation dates, history window) and a measur...

SERVERTengu SOURCEHlobo-dev/tengu-mcp
Low RISK CLASS
Category Read
Parameters 00 required
Recommended Allowedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/tengu-mcp/tengu-v3-features-catalogue.md

What tengu_v3_features_catalogue does on Tengu

AI agents call tengu_v3_features_catalogue to retrieve information from Tengu without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why tengu_v3_features_catalogue is rated Low

Even though tengu_v3_features_catalogue only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.

Risk signalsBulk/mass operation — affects multiple targets

Questions about tengu_v3_features_catalogue

What does the tengu_v3_features_catalogue tool do? +

FEATURE-STORE CATALOGUE — the derived research panels this platform computes for its own models: what exists, how much of it there is, how far back it goes, and how fresh it actually is. Every entry carries MEASURED coverage (rows, symbols, distinct observation dates, history window) and a measured freshness block. freshness.status is current when the producer is inside twice its own declared cadence, or archival when the producer has stopped but the dataset is a genuine historical panel — an archival dataset is still readable and EVERY read of it says so. A second, independent flag, stale_for_its_own_cadence, fires when the newest observation is old relative to the table's own typical gap: it catches a panel rewritten nightly whose data still ends months ago because the upstream licence lags. Datasets whose producer stopped and which are NOT panels are listed under withheld with the measurement that disqualified them and have NO route at all; excluded lists live datasets deliberately not sold here, with the reason. Live-measured 2026-08-02: 19 servable datasets totalling 17,062,613 rows — 14 current, 5 archival (spanning 1962, 1970, 2000, 2025-05 and 2026-05 forward) — plus 5 withheld and 2 excluded. Call it first: it is the only place the slugs for /api/v3/features/{dataset} are published. It is categorised as a Read tool in the Tengu MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on tengu_v3_features_catalogue? +

Register the Tengu MCP server in PolicyLayer and add a rule for tengu_v3_features_catalogue: 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 Tengu. Nothing to install.

What risk level is tengu_v3_features_catalogue? +

tengu_v3_features_catalogue is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit tengu_v3_features_catalogue? +

Yes. Add a rate_limit block to the tengu_v3_features_catalogue 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 tengu_v3_features_catalogue completely? +

Set action: deny in the PolicyLayer policy for tengu_v3_features_catalogue. 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 tengu_v3_features_catalogue? +

tengu_v3_features_catalogue is provided by the Tengu MCP server (Hlobo-dev/tengu-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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