ai_filters_list
List all AI filters for the current workspace. AI filters are semantic intent-based message filters that use embeddings (vector representations) to detect whether an incoming message matches a specific intent or topic. Unlike keyword filters, they understand meaning: 'I need help with my order' a...
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What ai_filters_list does on Dialogbrain
AI agents call ai_filters_list to retrieve information from Dialogbrain without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why ai_filters_list is rated Low
This tool performs a simple data retrieval operation that lists existing AI filter configurations. It has no side effects, does not modify or delete data, and does not trigger external operations. It falls cleanly into the Read category as a query/list operation.
From the tool's definition Tool name is 'ai_filters_list' and description explicitly states 'List all AI filters for the current workspace.' The function retrieves and queries configuration data without modifying, deleting, or executing any actions.
Attacks that exploit this kind of access
The rule that runs ai_filters_list safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For ai_filters_list, this is the rule to start with:
ai_filters_list 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 Dialogbrain, apply this rule, and every ai_filters_list call is checked against it from then on.
Questions about ai_filters_list
List all AI filters for the current workspace. AI filters are semantic intent-based message filters that use embeddings (vector representations) to detect whether an incoming message matches a specific intent or topic. Unlike keyword filters, they understand meaning: 'I need help with my order' and 'my package hasn't arrived' both match a 'shipping support' filter even without shared keywords. Each filter stores a reference embedding of its description. When a message arrives, its embedding is compared via cosine similarity against the filter's reference vector. If the similarity exceeds the threshold, the filter matches. When to use: - Check which semantic filters already exist before creating a new one - Get filter IDs for use in trigger conditions - Review thresholds and active status of existing filters Returns all filters with id, name, description, threshold, and is_active. It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for ai_filters_list: 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 Dialogbrain. Nothing to install.
ai_filters_list 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 ai_filters_list 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 ai_filters_list. 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.
ai_filters_list is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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