contacts_find

👤 Search for contacts in your address book by name or username. When to use: - User asks 'find contact X' or 'who is Y?' - User wants to know someone's username or ID - Before sending a message to verify contact exists - To get contact's channel reference for messaging Examples: ❓ User: 'find co...

SERVERDialogbrain SOURCEhttps://api.dialogbrain.com/mcp
Low RISK CLASS
Category Read
Parameters 31 required
Recommended Allowedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-saloprj-dialogbrain/contacts-find.md

What contacts_find does on Dialogbrain

AI agents call contacts_find 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.

ParameterTypeRequiredDescription
limit integer Maximum number of results to return
query string Yes Name or username to search for (supports partial matches)
channel string Filter by channel. OMIT to search across all channels.

Parameters from the server's own tool schema.

Why contacts_find is rated Low

This is a read-only operation that queries an address book and returns contact metadata. It retrieves data without creating, modifying, deleting, or executing any operations. The tool has minimal blast radius even if misused—an agent could enumerate contacts but cannot access message content, modify contacts, or trigger external actions.

From the tool's definition Tool description states 'Search for contacts in your address book by name or username' and 'Returns: name, username, channel, channel_ref, similarity_score, match_type.' The use cases all involve querying/retrieving contact information with no modification or…

Questions about contacts_find

What does the contacts_find tool do? +

👤 Search for contacts in your address book by name or username. When to use: - User asks 'find contact X' or 'who is Y?' - User wants to know someone's username or ID - Before sending a message to verify contact exists - To get contact's channel reference for messaging Examples: ❓ User: 'find contact named [name]' → contacts_search(query='[name]', limit=5) ❓ User: 'who is [full name]?' → contacts_search(query='[full name]', limit=1) ❓ User: 'search for @username' → contacts_search(query='username', limit=10) Returns: name, username, channel, channel_ref, similarity_score, match_type. Plus: - entity_id: local DB key — pass to contacts.profile. Null for live-discovered contacts (skip contacts.profile for those). - telegram_user_id (when channel='telegram'): the Telegram user ID — pass to calls.make / messages.send. NOT entity_id. It is categorised as a Read tool in the Dialogbrain MCP Server, which means it retrieves data without modifying state.

What parameters does contacts_find accept? +

contacts_find accepts 3 parameters: limit, query, channel. Required: query. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on contacts_find? +

Register the Dialogbrain MCP server in PolicyLayer and add a rule for contacts_find: 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.

What risk level is contacts_find? +

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

Can I rate-limit contacts_find? +

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

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

contacts_find 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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