Retrieve score configuration definitions. Includes available scores, their types, and descriptions. and score ids.
AI agents call get_score_configs to retrieve information from Langfuse Mcp Python without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves metadata about score configurations without creating, modifying, deleting, or executing any operations. It is a straightforward read operation with no side effects, making it the lowest-risk category.
From the tool's definition Tool name includes 'get_' prefix and description uses 'Retrieve' verb. Stated purpose is to fetch 'score configuration definitions' including 'available scores, their types, and descriptions and score ids'—purely informational operations with no modification,…
Attacks that exploit this kind of access
Retrieve score configuration definitions. Includes available scores, their types, and descriptions. and score ids. It is categorised as a Read tool in the Langfuse Mcp Python MCP Server, which means it retrieves data without modifying state.
Register the Langfuse Mcp Python MCP server in PolicyLayer and add a rule for get_score_configs: 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 Langfuse Mcp Python. Nothing to install.
get_score_configs 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_score_configs 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_score_configs. 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_score_configs is provided by the Langfuse Mcp Python MCP server (log-logn/langfuse-mcp-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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