extract_structured_data

Extract structured JSON data from unstructured text using an LLM. Provide the text and a description of the fields you want extracted. Returns validated JSON matching your schema. Useful for turning research findings, web pages, or documents into structured data.

SERVERNodebench SOURCEnodebench-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/io-github-homenshum-nodebench/extract-structured-data.md

What extract_structured_data does on Nodebench

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

Why extract_structured_data is rated Low

This tool reads and parses unstructured input to produce structured output. It performs no writes, deletes, code execution, or financial operations. The LLM processes text to validate against a provided schema, but the underlying operation is a read/retrieval of information from text. Confidence is high because the description clearly limits scope to extraction and parsing with no side effects mentioned.

From the tool's definition Tool description states it 'Extract[s] structured JSON data from unstructured text' and 'turning research findings, web pages, or documents into structured data.' The verb 'extract' indicates data retrieval/transformation without modification of source data.

Questions about extract_structured_data

What does the extract_structured_data tool do? +

Extract structured JSON data from unstructured text using an LLM. Provide the text and a description of the fields you want extracted. Returns validated JSON matching your schema. Useful for turning research findings, web pages, or documents into structured data. It is categorised as a Read tool in the Nodebench MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on extract_structured_data? +

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

What risk level is extract_structured_data? +

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

Can I rate-limit extract_structured_data? +

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

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

extract_structured_data is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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