Retrieve a specific knowledge unit by ID. Returns the full raw markdown with YAML frontmatter, inline source citations, and use-case recommendations. Prepends quality warning if the unit has open issues.
AI agents call get_unit to retrieve information from Knowledgelib without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only retrieves and returns existing knowledge content by ID. It has no side effects—it does not create, modify, delete, or execute any operations. The prepended quality warning is informational only. The blast radius of misuse is minimal; an attacker could only access existing knowledge units, not alter data or trigger external actions.
From the tool's definition Tool name is 'get_unit' and description states it 'Retrieve[s] a specific knowledge unit by ID' and 'Returns the full raw markdown with YAML frontmatter, inline source citations, and use-case recommendations.' The verb 'retrieve' and 'returns' indicate…
Attacks that exploit this kind of access
Retrieve a specific knowledge unit by ID. Returns the full raw markdown with YAML frontmatter, inline source citations, and use-case recommendations. Prepends quality warning if the unit has open issues. It is categorised as a Read tool in the Knowledgelib MCP Server, which means it retrieves data without modifying state.
Register the Knowledgelib MCP server in PolicyLayer and add a rule for get_unit: 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 Knowledgelib. Nothing to install.
get_unit 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 get_unit 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 get_unit. 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.
get_unit is provided by the Knowledgelib MCP server (peterbeck111/knowledgelib-io). 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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