validate_data

Validate columns against rules for min/max range, data type, nullability, uniqueness, and regex patterns.

SERVERCLIO Adios SOURCEpypi:clio-kit
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-iowarp-adios-mcp/validate-data.md

What validate_data does on CLIO Adios

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

Why validate_data is rated Low

The tool inspects data to verify it conforms to specified constraints (min/max range, data type, nullability, uniqueness, regex patterns). This is purely analytical with no side effects. It retrieves and analyzes data properties but does not create, modify, delete, or execute operations. Misuse risk is minimal since validation cannot corrupt data or trigger unintended external actions.

From the tool's definition Tool description states 'Validate columns against rules' — validation is a read-only operation that checks data properties without modifying, deleting, or executing arbitrary code. No mutation, destruction, or execution of external operations is described.

Questions about validate_data

What does the validate_data tool do? +

Validate columns against rules for min/max range, data type, nullability, uniqueness, and regex patterns. It is categorised as a Read tool in the CLIO Adios MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on validate_data? +

Register the CLIO Adios MCP server in PolicyLayer and add a rule for validate_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 CLIO Adios. Nothing to install.

What risk level is validate_data? +

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

Can I rate-limit validate_data? +

Yes. Add a rate_limit block to the validate_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 validate_data completely? +

Set action: deny in the PolicyLayer policy for validate_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 validate_data? +

validate_data is provided by the CLIO Adios MCP server (pypi:clio-kit). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

More on CLIO Adios, and thousands of servers like it.

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