Skip to main content
Glama

search_messages

Search all locally stored Signal messages by keyword or phrase to locate specific messages across conversations. Results are ranked by relevance and can be filtered by sender.

Instructions

Full-text search across all locally stored messages by keyword or phrase. Searches message bodies using SQLite FTS — results are ranked by relevance. Only messages in the local store are searchable; messages never received on this device are excluded. Use sender to narrow results to a specific conversation. Use limit and offset to paginate through large result sets. Use when looking for a specific message or topic across all Signal conversations. Do NOT use to browse a conversation chronologically — use get_conversation for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesKeyword or phrase to search for
senderNoFilter results to messages from this phone number (E.164)
limitNoMaximum results to return (default 50)
offsetNoSkip this many results for pagination (default 0)
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that search uses SQLite FTS, results are relevance-ranked, only locally stored messages are searched, and pagination is available. No annotations provided, but description covers behavioral traits thoroughly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Six sentences, front-loaded with core purpose, then technical details, then usage guidance. No redundant or unclear statements.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, constraints, parameters, and usage thoroughly. Lacks output format details but is essentially complete for a standard search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good descriptions; description adds context like E.164 format for sender and pagination usage, exceeding minimal baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs full-text search across locally stored messages by keyword or phrase, and distinguishes itself from chronological browsing via get_conversation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (searching for specific messages/topics across conversations) and when not to (use get_conversation for chronological browsing), with parameters like sender, limit, offset explained.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/googlarz/signal-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server