extract_entities
Extract named entities (people, places, orgs, dates) from text.
This record as markdown: /tools/io-github-scotia1973-bot-api-hub/extract-entities.md
What extract_entities does on GadgetHumans API Hub
AI agents call extract_entities to retrieve information from GadgetHumans API Hub without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why extract_entities is rated Low
This tool only reads and parses input text to identify and return structured entity data. It has no side effects, does not modify data, execute code, delete anything, or involve financial operations. The output is purely informational analysis. Misuse by an AI agent would be limited to extracting entities from sensitive text, but the tool itself cannot cause irreversible damage or access restricted systems.
From the tool's definition Tool performs text analysis to 'extract named entities (people, places, orgs, dates) from text' — a retrieval and classification operation with no modification, deletion, or execution of external systems.
Attacks that exploit this kind of access
The rule that runs extract_entities safely
PolicyLayer is an MCP gateway: it sits between your AI agents and GadgetHumans API Hub, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For extract_entities, this is the rule to start with:
extract_entities is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect GadgetHumans API Hub, apply this rule, and every extract_entities call is checked against it from then on.
Questions about extract_entities
Extract named entities (people, places, orgs, dates) from text. It is categorised as a Read tool in the GadgetHumans API Hub MCP Server, which means it retrieves data without modifying state.
Register the GadgetHumans API Hub MCP server in PolicyLayer and add a rule for extract_entities: 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 GadgetHumans API Hub. Nothing to install.
extract_entities 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 extract_entities 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 extract_entities. 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.
extract_entities is provided by the GadgetHumans API Hub MCP server (pypi:gadgethumans-api-hub-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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